----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\scheve\Dropbox\war\WarMobilizationFinancingProject\RailroadPaper\Analysis\JEH_Replication_2\OSS_mobil_replication.log
  log type:  text
 opened on:  26 Nov 2013, 13:44:33

. /* Replication of analyses in Journal of Economic History article "Technology and the Era of the Mass Army" */
. /* By Massimiliano Onorato, Ken Scheve, David Stasavage*/
. /* November 2013 */
. 
. # delimit;clear;
delimiter now ;
. use "OSS_mobil_repl_data.dta", clear;

. set mat 1000;

. sort countryno year;

. xtset countryno year;
       panel variable:  countryno (unbalanced)
        time variable:  year, 1600 to 2000
                delta:  1 unit

. /***************
> Replication of analyses reported in the article
> *****************/
> 
> /***************
> Replication of Table 1
> *****************/
> summarize mobil military1 if year>=1600 & year<1700 & waryear==1;

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
       mobil |        69    .0176686     .025102   .0015306   .1902174
   military1 |        69    95.36986    62.22455         13        362

. summarize mobil military1 if year>=1700 & year<1800 & waryear==1;

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
       mobil |       152    .0157045     .010793   .0023565   .0823239
   military1 |       152    179.5586    102.3509     12.725    732.474

. summarize mobil military1 if year>=1800 & year<1900 & waryear==1;

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
       mobil |        80    .0165368    .0088179   .0022646   .0540672
   military1 |        80    481.5158    324.0112     11.134       2000

. summarize mobil military1 if year>=1900 & year<=2000 & waryear==1;

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
       mobil |       142    .0344576    .0364859   .0016547   .1607371
   military1 |       142    2762.583    2546.014    125.923      12500

. /***************
> Replication of Table 2
> *****************/
> 
> xtreg military1  gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2267                         Obs per group: min =         5
       between = 0.6434                                        avg =      34.1
       overall = 0.3386                                        max =       109

                                                F(3,12)            =     11.32
corr(u_i, Xb)  = 0.2242                         Prob > F           =    0.0008

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
   military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gt1789 |  -23.92975   138.4416    -0.17   0.866    -325.5681    277.7086
      gt1859 |   2030.983   545.0373     3.73   0.003     843.4491    3218.517
      gt1970 |  -1166.186   448.3736    -2.60   0.023    -2143.108   -189.2639
       _cons |   349.0531   143.9275     2.43   0.032     35.46214    662.6441
-------------+----------------------------------------------------------------
     sigma_u |   792.3856
     sigma_e |  1416.1403
         rho |  .23843397   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3577                         Obs per group: min =         5
       between = 0.4250                                        avg =      34.1
       overall = 0.2563                                        max =       109

                                                F(5,12)            =    263.07
corr(u_i, Xb)  = -0.9324                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   43707.09   11831.45     3.69   0.003     17928.59     69485.6
firstcruise_lib |  -427.2783   271.8251    -1.57   0.142    -1019.534    164.9777
         gt1789 |   96.67412   83.74648     1.15   0.271    -85.79379     279.142
         gt1859 |   219.1592   477.4698     0.46   0.654    -821.1581    1259.476
         gt1970 |   353.2559   339.7855     1.04   0.319    -387.0731    1093.585
          _cons |  -426.4864   241.1075    -1.77   0.102    -951.8145    98.84173
----------------+----------------------------------------------------------------
        sigma_u |  3360.1348
        sigma_e |  1293.6415
            rho |  .87091126   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4400                         Obs per group: min =         5
       between = 0.6889                                        avg =      34.1
       overall = 0.3259                                        max =       109

                                                F(7,12)            =    325.48
corr(u_i, Xb)  = -0.9292                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   35002.65   5297.878     6.61   0.000     23459.57    46545.74
firstcruise_lib |  -3689.954   637.6629    -5.79   0.000    -5079.302   -2300.606
         popul1 |   .0127968   .0024371     5.25   0.000     .0074868    .0181067
        gdppcip |    .306215   .1286695     2.38   0.035     .0258682    .5865618
   literacy_qrt |  -78.38179   110.4242    -0.71   0.491    -318.9755    162.2119
      democracy |  -630.8632   540.2735    -1.17   0.266    -1808.018    546.2916
           year |  -1.421403   1.369563    -1.04   0.320    -4.405424    1.562618
          _cons |   1570.326   2250.961     0.70   0.499    -3334.096    6474.748
----------------+----------------------------------------------------------------
        sigma_u |  3318.8846
        sigma_e |  1210.7751
            rho |   .8825431   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend rus
> siatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4641                         Obs per group: min =         5
       between = 0.2150                                        avg =      34.1
       overall = 0.0092                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   31969.21   2588.817    12.35   0.000     26328.66    37609.76
    firstcruise_lib |  -3264.737   1004.757    -3.25   0.007    -5453.914   -1075.559
             popul1 |   .0228253   .0162063     1.41   0.184    -.0124852    .0581357
            gdppcip |   .1975507   .1627641     1.21   0.248    -.1570818    .5521833
       literacy_qrt |  -92.40057   199.9211    -0.46   0.652    -527.9912    343.1901
          democracy |    -111.13   367.8341    -0.30   0.768    -912.5716    690.3116
austriahungarytrend |  -1.742852   .6767586    -2.58   0.024    -3.217383   -.2683221
         chinatrend |  -203.1999   252.8684    -0.80   0.437    -754.1528    347.7529
        francetrend |  -2.012804     1.6619    -1.21   0.249    -5.633773    1.608164
         italytrend |   2.094299    4.76751     0.44   0.668    -8.293213    12.48181
         japantrend |   41.78844    11.1554     3.75   0.003     17.48292    66.09397
   netherlandstrend |  -1.103995   1.308007    -0.84   0.415    -3.953897    1.745908
       germanytrend |   4.515208   5.389733     0.84   0.419     -7.22801    16.25843
        russiatrend |  -10.13296   12.27479    -0.83   0.425    -36.87743    16.61151
         spaintrend |  -2.112706    .096778   -21.83   0.000    -2.323567   -1.901844
        swedentrend |   2.654593   5.515423     0.48   0.639    -9.362482    14.67167
           usatrend |   2.916337   28.65751     0.10   0.921    -59.52301    65.35568
            uktrend |  -3.197277   1.599354    -2.00   0.069     -6.68197    .2874162
          ottotrend |   1.412044   .7171329     1.97   0.072    -.1504543    2.974543
              _cons |   5099.375   13151.13     0.39   0.705    -23554.49    33753.24
--------------------+----------------------------------------------------------------
            sigma_u |  111471.16
            sigma_e |  1201.6414
                rho |  .99988381   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /***************
> Replication of Table 3
> *****************/
> 
> xtreg mobil  gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1411                         Obs per group: min =         5
       between = 0.0167                                        avg =      34.1
       overall = 0.1076                                        max =       109

                                                F(3,12)            =     11.73
corr(u_i, Xb)  = -0.2168                        Prob > F           =    0.0007

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
       mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gt1789 |   .0028946   .0024621     1.18   0.263    -.0024699     .008259
      gt1859 |     .02078   .0037536     5.54   0.000     .0126015    .0289584
      gt1970 |   -.020103   .0059959    -3.35   0.006    -.0331669   -.0070391
       _cons |   .0135216   .0016604     8.14   0.000     .0099039    .0171393
-------------+----------------------------------------------------------------
     sigma_u |  .02259887
     sigma_e |  .02165074
         rho |  .52141701   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1614                         Obs per group: min =         5
       between = 0.0138                                        avg =      34.1
       overall = 0.0359                                        max =       109

                                                F(5,12)            =     74.13
corr(u_i, Xb)  = -0.7646                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2242763   .1061935     2.11   0.056    -.0070994     .455652
firstcruise_lib |   -.013293   .0026322    -5.05   0.000    -.0190281   -.0075579
         gt1789 |   .0034903   .0021774     1.60   0.135    -.0012539    .0082344
         gt1859 |   .0116665     .00392     2.98   0.012     .0031256    .0202073
         gt1970 |  -.0027335   .0043988    -0.62   0.546    -.0123178    .0068507
          _cons |   .0097075    .002824     3.44   0.005     .0035545    .0158605
----------------+----------------------------------------------------------------
        sigma_u |  .03148031
        sigma_e |  .02144436
            rho |  .68304509   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1921                         Obs per group: min =         5
       between = 0.0265                                        avg =      34.1
       overall = 0.0346                                        max =       109

                                                F(7,12)            =    920.40
corr(u_i, Xb)  = -0.7859                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2046159    .074677     2.74   0.018     .0419087    .3673232
firstcruise_lib |  -.0310548   .0091797    -3.38   0.005    -.0510556   -.0110541
         popul2 |   .0348975   .0407962     0.86   0.409    -.0539898    .1237849
       gdppcip2 |   .0012345   .0014961     0.83   0.425    -.0020251    .0044941
   literacy_qrt |    .000637   .0033941     0.19   0.854    -.0067581    .0080321
      democracy |   .0130481   .0046511     2.81   0.016     .0029141     .023182
           year |   .0000169   .0000186     0.91   0.381    -.0000236    .0000574
          _cons |  -.0219828   .0288826    -0.76   0.461    -.0849127     .040947
----------------+----------------------------------------------------------------
        sigma_u |  .03404673
        sigma_e |  .02109696
            rho |  .72256279   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russia
> trend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2282                         Obs per group: min =         5
       between = 0.1469                                        avg =      34.1
       overall = 0.0019                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |    .297664    .111254     2.68   0.020     .0552623    .5400656
    firstcruise_lib |  -.0296438    .009559    -3.10   0.009    -.0504711   -.0088164
             popul2 |  -.1022848   .2673079    -0.38   0.709    -.6846987    .4801291
           gdppcip2 |   .0002829   .0013824     0.20   0.841    -.0027289    .0032948
       literacy_qrt |     .00187   .0054582     0.34   0.738    -.0100224    .0137624
          democracy |   .0136457   .0018824     7.25   0.000     .0095442    .0177471
austriahungarytrend |   .0000191   .0000187     1.02   0.327    -.0000217    .0000599
         chinatrend |   .0021678   .0035854     0.60   0.557    -.0056442    .0099797
        francetrend |   .0000382   .0000372     1.03   0.324    -.0000428    .0001193
         italytrend |   .0001261   .0001384     0.91   0.380    -.0001754    .0004277
         japantrend |   .0009482   .0002183     4.34   0.001     .0004725    .0014238
   netherlandstrend |   .0002428   .0000118    20.53   0.000     .0002171    .0002686
       germanytrend |   .0001159   .0000874     1.33   0.209    -.0000745    .0003063
        russiatrend |   8.49e-07   .0001762     0.00   0.996    -.0003831    .0003848
         spaintrend |  -.0002398   1.70e-06  -140.97   0.000    -.0002435   -.0002361
        swedentrend |  -.0002323   .0001501    -1.55   0.148    -.0005593    .0000948
           usatrend |    .000782   .0005967     1.31   0.215     -.000518     .002082
            uktrend |   .0000256    .000023     1.11   0.289    -.0000246    .0000758
          ottotrend |   .0000318   .0000103     3.08   0.009     9.34e-06    .0000544
              _cons |  -.2714054    .208234    -1.30   0.217    -.7251083    .1822975
--------------------+----------------------------------------------------------------
            sigma_u |  1.2724856
            sigma_e |  .02091956
                rho |   .9997298   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /***************
> Replication of Table 4
> *****************/  
> 
> clear;

. use OSS_mobil_repl_data_lrgesmple.dta, replace;

. xtset uniqueccode year;
       panel variable:  uniqueccode (unbalanced)
        time variable:  year, 1816 to 2000, but with gaps
                delta:  1 unit

. xtreg milper raillineip pctivliteracyip tpop rgdppcip democracy year if waryear==1, fe cluster(uniqueccode);

Fixed-effects (within) regression               Number of obs      =       601
Group variable: uniqueccode                     Number of groups   =        60

R-sq:  within  = 0.2235                         Obs per group: min =         1
       between = 0.2489                                        avg =      10.0
       overall = 0.2440                                        max =        39

                                                F(6,59)            =     13.45
corr(u_i, Xb)  = -0.3181                        Prob > F           =    0.0000

                              (Std. Err. adjusted for 60 clusters in uniqueccode)
---------------------------------------------------------------------------------
                |               Robust
         milper |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
     raillineip |   10998.81   3749.792     2.93   0.005     3495.491    18502.12
pctivliteracyip |   .2128348   1.452448     0.15   0.884    -2.693507    3.119176
           tpop |   .0023667   .0010825     2.19   0.033     .0002006    .0045328
       rgdppcip |  -68.02338   49.78451    -1.37   0.177    -167.6419    31.59519
      democracy |   106.5475   222.6308     0.48   0.634    -338.9358    552.0307
           year |   10.66556   9.371409     1.14   0.260    -8.086588    29.41771
          _cons |  -20148.92   17186.48    -1.17   0.246       -54539    14241.15
----------------+----------------------------------------------------------------
        sigma_u |  743.71126
        sigma_e |  1190.2503
            rho |  .28079287   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg milper raillineip pctivliteracyip tpop rgdppcip democracy cd1-cd100 if waryear==1, fe cluster(uniqueccode);
note: cd4 omitted because of collinearity
note: cd5 omitted because of collinearity
note: cd10 omitted because of collinearity
note: cd11 omitted because of collinearity
note: cd12 omitted because of collinearity
note: cd14 omitted because of collinearity
note: cd15 omitted because of collinearity
note: cd22 omitted because of collinearity
note: cd24 omitted because of collinearity
note: cd28 omitted because of collinearity
note: cd33 omitted because of collinearity
note: cd36 omitted because of collinearity
note: cd42 omitted because of collinearity
note: cd43 omitted because of collinearity
note: cd45 omitted because of collinearity
note: cd46 omitted because of collinearity
note: cd47 omitted because of collinearity
note: cd48 omitted because of collinearity
note: cd49 omitted because of collinearity
note: cd50 omitted because of collinearity
note: cd51 omitted because of collinearity
note: cd52 omitted because of collinearity
note: cd53 omitted because of collinearity
note: cd54 omitted because of collinearity
note: cd55 omitted because of collinearity
note: cd56 omitted because of collinearity
note: cd59 omitted because of collinearity
note: cd64 omitted because of collinearity
note: cd65 omitted because of collinearity
note: cd67 omitted because of collinearity
note: cd69 omitted because of collinearity
note: cd70 omitted because of collinearity
note: cd71 omitted because of collinearity
note: cd73 omitted because of collinearity
note: cd74 omitted because of collinearity
note: cd75 omitted because of collinearity
note: cd76 omitted because of collinearity
note: cd82 omitted because of collinearity
note: cd90 omitted because of collinearity
note: cd91 omitted because of collinearity
note: cd92 omitted because of collinearity
note: cd96 omitted because of collinearity
note: cd98 omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       601
Group variable: uniqueccode                     Number of groups   =        60

R-sq:  within  = 0.3326                         Obs per group: min =         1
       between = 0.0170                                        avg =      10.0
       overall = 0.0174                                        max =        39

                                                F(5,59)            =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                              (Std. Err. adjusted for 60 clusters in uniqueccode)
---------------------------------------------------------------------------------
                |               Robust
         milper |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
     raillineip |   7225.407   1985.857     3.64   0.001     3251.716     11199.1
pctivliteracyip |   1.963955   1.328481     1.48   0.145    -.6943304     4.62224
           tpop |    .002305   .0023366     0.99   0.328    -.0023704    .0069805
       rgdppcip |  -58.00623   82.58641    -0.70   0.485    -223.2613    107.2488
      democracy |   291.0218   294.6389     0.99   0.327    -298.5492    880.5928
            cd1 |    10.7312   10.61301     1.01   0.316    -10.50539    31.96779
            cd2 |   9.288617   20.89708     0.44   0.658    -32.52635    51.10358
            cd3 |  -9.699008   13.09116    -0.74   0.462    -35.89436    16.49635
            cd4 |          0  (omitted)
            cd5 |          0  (omitted)
            cd6 |   .1915633   .2003217     0.96   0.343    -.2092795     .592406
            cd7 |   -4.06477   2.657097    -1.53   0.131    -9.381609     1.25207
            cd8 |  -8.812943   7.197113    -1.22   0.226    -23.21433    5.588447
            cd9 |  -11.54906   7.601417    -1.52   0.134    -26.75946    3.661339
           cd10 |          0  (omitted)
           cd11 |          0  (omitted)
           cd12 |          0  (omitted)
           cd13 |  -4.119208   3.665382    -1.12   0.266    -11.45362    3.215205
           cd14 |          0  (omitted)
           cd15 |          0  (omitted)
           cd16 |  -10.75307    6.58276    -1.63   0.108    -23.92514    2.419001
           cd17 |  -7.236776   6.365093    -1.14   0.260     -19.9733    5.499746
           cd18 |  -13.90795   9.895431    -1.41   0.165    -33.70866    5.892765
           cd19 |  -14.93403   9.346008    -1.60   0.115    -33.63535     3.76729
           cd20 |  -18.48733   14.60648    -1.27   0.211    -47.71483    10.74017
           cd21 |  -2.187362   4.795303    -0.46   0.650    -11.78274    7.408017
           cd22 |          0  (omitted)
           cd23 |   3.183769   7.802869     0.41   0.685    -12.42974    18.79727
           cd24 |          0  (omitted)
           cd25 |   6.146779   20.98586     0.29   0.771    -35.84582    48.13938
           cd26 |  -2.361811   5.244033    -0.45   0.654     -12.8551    8.131474
           cd27 |   2.726237   8.180786     0.33   0.740    -13.64348    19.09595
           cd28 |          0  (omitted)
           cd29 |  -6.627805   3.808284    -1.74   0.087    -14.24816    .9925544
           cd30 |  -7.380138    5.36321    -1.38   0.174     -18.1119    3.351621
           cd31 |   58.30542   2.581601    22.58   0.000     53.13965    63.47119
           cd32 |   622.8888   14.31938    43.50   0.000     594.2358    651.5418
           cd33 |          0  (omitted)
           cd34 |   2.108024   4.581235     0.46   0.647    -7.059006    11.27505
           cd35 |  -10.53082   10.85846    -0.97   0.336    -32.25856    11.19691
           cd36 |          0  (omitted)
           cd37 |  -15.29664    10.1467    -1.51   0.137    -35.60015    5.006871
           cd38 |   77.53421   15.16561     5.11   0.000      47.1879    107.8805
           cd39 |   8.972242   12.56584     0.71   0.478    -16.17195    34.11643
           cd40 |    19.3506   6.887161     2.81   0.007     5.569422    33.13177
           cd41 |  -2.799147   10.40063    -0.27   0.789    -23.61075    18.01246
           cd42 |          0  (omitted)
           cd43 |          0  (omitted)
           cd44 |   2.081067   3.592123     0.58   0.565    -5.106754    9.268889
           cd45 |          0  (omitted)
           cd46 |          0  (omitted)
           cd47 |          0  (omitted)
           cd48 |          0  (omitted)
           cd49 |          0  (omitted)
           cd50 |          0  (omitted)
           cd51 |          0  (omitted)
           cd52 |          0  (omitted)
           cd53 |          0  (omitted)
           cd54 |          0  (omitted)
           cd55 |          0  (omitted)
           cd56 |          0  (omitted)
           cd57 |  -25.63725   16.50408    -1.55   0.126    -58.66184    7.387333
           cd58 |  -36.82003    25.5244    -1.44   0.154    -87.89424    14.25417
           cd59 |          0  (omitted)
           cd60 |  -123.8475   74.88637    -1.65   0.103    -273.6948    25.99974
           cd61 |  -1.166977   1.058134    -1.10   0.275    -3.284299    .9503448
           cd62 |  -8.481812   5.960553    -1.42   0.160    -20.40885    3.445228
           cd63 |  -20.16216   11.63466    -1.73   0.088    -43.44307    3.118743
           cd64 |          0  (omitted)
           cd65 |          0  (omitted)
           cd66 |  -14.94793   8.775936    -1.70   0.094    -32.50854    2.612679
           cd67 |          0  (omitted)
           cd68 |   27.37344   5.096546     5.37   0.000     17.17527     37.5716
           cd69 |          0  (omitted)
           cd70 |          0  (omitted)
           cd71 |          0  (omitted)
           cd72 |  -3.619537   2.899813    -1.25   0.217    -9.422051    2.182976
           cd73 |          0  (omitted)
           cd74 |          0  (omitted)
           cd75 |          0  (omitted)
           cd76 |          0  (omitted)
           cd77 |     -7.204   5.088302    -1.42   0.162    -17.38567     2.97767
           cd78 |  -2.283793   4.037347    -0.57   0.574    -10.36251     5.79492
           cd79 |   8.310198   10.98498     0.76   0.452    -13.67069    30.29108
           cd80 |  -3.495713   7.513611    -0.47   0.643    -18.53041    11.53899
           cd81 |  -3.825793   14.91183    -0.26   0.798    -33.66429     26.0127
           cd82 |          0  (omitted)
           cd83 |   10.19811   21.97517     0.46   0.644     -33.7741    54.17033
           cd84 |  -8.239327   20.17211    -0.41   0.684    -48.60363    32.12498
           cd85 |  -.1182165    10.5396    -0.01   0.991     -21.2079    20.97147
           cd86 |   3.897873    12.3068     0.32   0.753    -20.72797    28.52372
           cd87 |   42.49859   3.327777    12.77   0.000     35.83972    49.15745
           cd88 |  -40.02513    27.8173    -1.44   0.155    -95.68741    15.63715
           cd89 |  -11.64639   9.469566    -1.23   0.224    -30.59495    7.302163
           cd90 |          0  (omitted)
           cd91 |          0  (omitted)
           cd92 |          0  (omitted)
           cd93 |   8.668973   5.040757     1.72   0.091    -1.417559     18.7555
           cd94 |  -2.643462   17.86042    -0.15   0.883    -38.38207    33.09515
           cd95 |  -3.302223   20.01478    -0.16   0.870    -43.35171    36.74726
           cd96 |          0  (omitted)
           cd97 |   -1.17376   17.28859    -0.07   0.946    -35.76815    33.42063
           cd98 |          0  (omitted)
           cd99 |   1.481708   15.39627     0.10   0.924    -29.32617    32.28958
          cd100 |   2.923977   10.79541     0.27   0.787    -18.67759    24.52555
          _cons |   -9140.06   10621.03    -0.86   0.393    -30392.69    12112.57
----------------+----------------------------------------------------------------
        sigma_u |   162043.1
        sigma_e |  1166.1952
            rho |  .99994821   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobilization raillineip pctivliteracyip tpop rgdppcip democracy year if waryear==1, fe cluster(uniqueccode);

Fixed-effects (within) regression               Number of obs      =       601
Group variable: uniqueccode                     Number of groups   =        60

R-sq:  within  = 0.0547                         Obs per group: min =         1
       between = 0.0041                                        avg =      10.0
       overall = 0.0111                                        max =        39

                                                F(6,59)            =      3.55
corr(u_i, Xb)  = -0.3892                        Prob > F           =    0.0045

                              (Std. Err. adjusted for 60 clusters in uniqueccode)
---------------------------------------------------------------------------------
                |               Robust
   mobilization |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
     raillineip |   .1062347   .0421349     2.52   0.014     .0219231    .1905464
pctivliteracyip |  -3.77e-06   .0000204    -0.19   0.854    -.0000445     .000037
           tpop |  -1.11e-08   1.91e-08    -0.58   0.562    -4.92e-08    2.70e-08
       rgdppcip |  -.0014272   .0006752    -2.11   0.039    -.0027782   -.0000761
      democracy |   .0123436   .0053318     2.32   0.024     .0016748    .0230124
           year |   .0001105   .0001076     1.03   0.309    -.0001048    .0003258
          _cons |  -.1930206   .1990431    -0.97   0.336    -.5913049    .2052637
----------------+----------------------------------------------------------------
        sigma_u |  .01625352
        sigma_e |   .0232965
            rho |  .32739569   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobilization raillineip pctivliteracyip tpop rgdppcip democracy cd1-cd100 if waryear==1, fe cluster(uniqueccode);
note: cd4 omitted because of collinearity
note: cd5 omitted because of collinearity
note: cd10 omitted because of collinearity
note: cd11 omitted because of collinearity
note: cd12 omitted because of collinearity
note: cd14 omitted because of collinearity
note: cd15 omitted because of collinearity
note: cd22 omitted because of collinearity
note: cd24 omitted because of collinearity
note: cd28 omitted because of collinearity
note: cd33 omitted because of collinearity
note: cd36 omitted because of collinearity
note: cd42 omitted because of collinearity
note: cd43 omitted because of collinearity
note: cd45 omitted because of collinearity
note: cd46 omitted because of collinearity
note: cd47 omitted because of collinearity
note: cd48 omitted because of collinearity
note: cd49 omitted because of collinearity
note: cd50 omitted because of collinearity
note: cd51 omitted because of collinearity
note: cd52 omitted because of collinearity
note: cd53 omitted because of collinearity
note: cd54 omitted because of collinearity
note: cd55 omitted because of collinearity
note: cd56 omitted because of collinearity
note: cd59 omitted because of collinearity
note: cd64 omitted because of collinearity
note: cd65 omitted because of collinearity
note: cd67 omitted because of collinearity
note: cd69 omitted because of collinearity
note: cd70 omitted because of collinearity
note: cd71 omitted because of collinearity
note: cd73 omitted because of collinearity
note: cd74 omitted because of collinearity
note: cd75 omitted because of collinearity
note: cd76 omitted because of collinearity
note: cd82 omitted because of collinearity
note: cd90 omitted because of collinearity
note: cd91 omitted because of collinearity
note: cd92 omitted because of collinearity
note: cd96 omitted because of collinearity
note: cd98 omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       601
Group variable: uniqueccode                     Number of groups   =        60

R-sq:  within  = 0.2214                         Obs per group: min =         1
       between = 0.1519                                        avg =      10.0
       overall = 0.0238                                        max =        39

                                                F(5,59)            =         .
corr(u_i, Xb)  = -1.0000                        Prob > F           =         .

                              (Std. Err. adjusted for 60 clusters in uniqueccode)
---------------------------------------------------------------------------------
                |               Robust
   mobilization |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
     raillineip |   .0420442   .0299485     1.40   0.166    -.0178826     .101971
pctivliteracyip |   .0000473   .0000362     1.31   0.197    -.0000252    .0001197
           tpop |  -2.04e-08   2.93e-08    -0.69   0.490    -7.90e-08    3.83e-08
       rgdppcip |  -.0018409   .0011655    -1.58   0.120     -.004173    .0004912
      democracy |   .0096475   .0067956     1.42   0.161    -.0039505    .0232455
            cd1 |   .0001929   .0001701     1.13   0.262    -.0001476    .0005334
            cd2 |  -.0000855   .0002959    -0.29   0.774    -.0006775    .0005066
            cd3 |   .0003684   .0003584     1.03   0.308    -.0003487    .0010854
            cd4 |          0  (omitted)
            cd5 |          0  (omitted)
            cd6 |   .0000128   3.58e-06     3.56   0.001     5.58e-06    .0000199
            cd7 |  -.0000323   .0000734    -0.44   0.662    -.0001791    .0001146
            cd8 |  -.0001916   .0001846    -1.04   0.304     -.000561    .0001778
            cd9 |  -.0002835   .0002087    -1.36   0.180    -.0007011    .0001341
           cd10 |          0  (omitted)
           cd11 |          0  (omitted)
           cd12 |          0  (omitted)
           cd13 |  -.0000812   .0000902    -0.90   0.371    -.0002616    .0000991
           cd14 |          0  (omitted)
           cd15 |          0  (omitted)
           cd16 |  -.0005598     .00018    -3.11   0.003      -.00092   -.0001997
           cd17 |   .0000558   .0001773     0.31   0.754    -.0002989    .0004105
           cd18 |  -.0002836   .0002045    -1.39   0.171    -.0006928    .0001256
           cd19 |   -.001296    .000257    -5.04   0.000    -.0018103   -.0007817
           cd20 |  -.0002334     .00038    -0.61   0.541    -.0009938     .000527
           cd21 |  -.0000198   .0000853    -0.23   0.817    -.0001905    .0001509
           cd22 |          0  (omitted)
           cd23 |   .0000424   .0001363     0.31   0.757    -.0002303    .0003151
           cd24 |          0  (omitted)
           cd25 |  -.0004974   .0002949    -1.69   0.097    -.0010875    .0000927
           cd26 |  -.0003334     .00008    -4.17   0.000    -.0004936   -.0001732
           cd27 |   .0001665   .0001536     1.08   0.283    -.0001408    .0004738
           cd28 |          0  (omitted)
           cd29 |  -.0001802   .0001049    -1.72   0.091    -.0003902    .0000298
           cd30 |  -.0001866   .0001425    -1.31   0.195    -.0004716    .0000985
           cd31 |   .0006426   .0000385    16.68   0.000     .0005655    .0007197
           cd32 |   .0228851   .0003633    63.00   0.000     .0221582     .023612
           cd33 |          0  (omitted)
           cd34 |   .0005228   .0001001     5.22   0.000     .0003224    .0007231
           cd35 |  -.0002812    .000216    -1.30   0.198    -.0007134    .0001511
           cd36 |          0  (omitted)
           cd37 |  -.0003329   .0002745    -1.21   0.230    -.0008822    .0002164
           cd38 |   .0192926   .0004143    46.56   0.000     .0184635    .0201217
           cd39 |   .0021198   .0003579     5.92   0.000     .0014037    .0028358
           cd40 |  -.0002048   .0002347    -0.87   0.386    -.0006746    .0002649
           cd41 |   .0017625   .0002613     6.74   0.000     .0012396    .0022855
           cd42 |          0  (omitted)
           cd43 |          0  (omitted)
           cd44 |   .0000621   .0000506     1.23   0.225    -.0000392    .0001634
           cd45 |          0  (omitted)
           cd46 |          0  (omitted)
           cd47 |          0  (omitted)
           cd48 |          0  (omitted)
           cd49 |          0  (omitted)
           cd50 |          0  (omitted)
           cd51 |          0  (omitted)
           cd52 |          0  (omitted)
           cd53 |          0  (omitted)
           cd54 |          0  (omitted)
           cd55 |          0  (omitted)
           cd56 |          0  (omitted)
           cd57 |  -.0005803   .0004819    -1.20   0.233    -.0015445     .000384
           cd58 |   -.000808   .0007045    -1.15   0.256    -.0022177    .0006016
           cd59 |          0  (omitted)
           cd60 |  -.0033676   .0020582    -1.64   0.107     -.007486    .0007508
           cd61 |  -.0002451   .0000329    -7.45   0.000     -.000311   -.0001793
           cd62 |  -.0002364   .0001809    -1.31   0.196    -.0005984    .0001256
           cd63 |  -.0007245   .0003281    -2.21   0.031    -.0013809    -.000068
           cd64 |          0  (omitted)
           cd65 |          0  (omitted)
           cd66 |  -.0004191   .0002288    -1.83   0.072    -.0008768    .0000387
           cd67 |          0  (omitted)
           cd68 |   .0024157   .0000743    32.49   0.000     .0022669    .0025645
           cd69 |          0  (omitted)
           cd70 |          0  (omitted)
           cd71 |          0  (omitted)
           cd72 |  -.0001704   .0000511    -3.34   0.001    -.0002725   -.0000682
           cd73 |          0  (omitted)
           cd74 |          0  (omitted)
           cd75 |          0  (omitted)
           cd76 |          0  (omitted)
           cd77 |  -.0001759   .0001476    -1.19   0.238    -.0004712    .0001193
           cd78 |   .0000302   .0000983     0.31   0.759    -.0001665     .000227
           cd79 |   .0009328   .0002974     3.14   0.003     .0003377    .0015278
           cd80 |  -.0000942   .0002172    -0.43   0.666    -.0005289    .0003405
           cd81 |   .0004891   .0003485     1.40   0.166    -.0002083    .0011864
           cd82 |          0  (omitted)
           cd83 |  -.0001561   .0003116    -0.50   0.618    -.0007795    .0004674
           cd84 |  -6.63e-07   .0003983    -0.00   0.999    -.0007976    .0007963
           cd85 |  -.0002272   .0002441    -0.93   0.356    -.0007157    .0002614
           cd86 |   .0000461   .0003121     0.15   0.883    -.0005784    .0006707
           cd87 |   .0006269   .0000564    11.11   0.000     .0005141    .0007398
           cd88 |  -.0000322   .0003881    -0.08   0.934    -.0008088    .0007445
           cd89 |  -.0003664   .0002382    -1.54   0.129     -.000843    .0001102
           cd90 |          0  (omitted)
           cd91 |          0  (omitted)
           cd92 |          0  (omitted)
           cd93 |    .000248   .0001267     1.96   0.055    -5.50e-06    .0005015
           cd94 |  -.0035444   .0004925    -7.20   0.000    -.0045298    -.002559
           cd95 |  -.0008465   .0006042    -1.40   0.166    -.0020555    .0003625
           cd96 |          0  (omitted)
           cd97 |   .0001641   .0004873     0.34   0.737     -.000811    .0011393
           cd98 |          0  (omitted)
           cd99 |  -.0011024   .0002181    -5.05   0.000    -.0015388    -.000666
          cd100 |  -.0025472   .0001528   -16.68   0.000    -.0028528   -.0022415
          _cons |  -.2095981   .2886801    -0.73   0.471    -.7872455    .3680494
----------------+----------------------------------------------------------------
        sigma_u |  7.6270783
        sigma_e |  .02234526
            rho |  .99999142   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. clear;

. /*************** 
> *Figure 1
> ****************/
> use "OSS_mobil_repl_data.dta", clear;

. sort countryno year;

. xtset countryno year;
       panel variable:  countryno (unbalanced)
        time variable:  year, 1600 to 2000
                delta:  1 unit

. twoway (connected military1 year if country=="France", yaxis(1) ytitle("Military Size, Thousands",axis(1)) msymbol(O) ylabel(0(1000)5000)) (connected mobil year if country=="Fr
> ance", yaxis(2) ytitle("Mobilization",axis(2))msymbol(Dh) ylabel(0(.05).40,axis(2))), xtitle(Year) title(Military Mobilization in France) graphregion(fcolor(white)) xline(1693)
>  text(3000 1693 "Nine Years'", place(c)) text(2600 1693 "War", place(c)) xline(1747) text(5000 1747 "War of Austrian", place(c)) text(4600 1747 "Succession", place(c)) xline(17
> 94) text(1900 1794 "Revolutionary", place(c)) text(1500 1794 "Wars", place(c))  xline(1812) text(3500 1812 "Napoleonic", place(c)) text(3100 1812 "Wars", place(c)) xline(1871) 
> text(2600 1871 "Franco-Prussian", place(c)) text(2200 1871 "War",place(c)) xline(1918) text(4000 1918 "WWI",place(c)) xline(1940) text(3000 1940 "WWII",place(c)) legend( order(
> 1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

. graph save Figure1,replace;
(file Figure1.gph saved)

. /***************
> Replication of Analyses Reported in text in the article
> *****************/
> 
> /** Rerun key specifications with gt1957 as alternative to gt1970 **/
> xtreg military1 gt1789 gt1859 gt1957 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2314                         Obs per group: min =         5
       between = 0.5597                                        avg =      34.1
       overall = 0.3223                                        max =       109

                                                F(3,12)            =     11.79
corr(u_i, Xb)  = 0.1871                         Prob > F           =    0.0007

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
   military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gt1789 |   -23.4768   138.1278    -0.17   0.868    -324.4315    277.4779
      gt1859 |   2035.484   543.4783     3.75   0.003     851.3469    3219.622
      gt1957 |  -1249.012   316.8068    -3.94   0.002    -1939.275   -558.7495
       _cons |   369.3141   142.2221     2.60   0.023     59.43881    679.1894
-------------+----------------------------------------------------------------
     sigma_u |  867.32932
     sigma_e |  1411.8366
         rho |  .27399323   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib gt1789 gt1859 gt1957 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3575                         Obs per group: min =         5
       between = 0.4240                                        avg =      34.1
       overall = 0.2585                                        max =       109

                                                F(5,12)            =     40.70
corr(u_i, Xb)  = -0.9300                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   42816.19   12225.58     3.50   0.004     16178.95    69453.43
firstcruise_lib |    125.117    1035.01     0.12   0.906    -2129.977    2380.211
         gt1789 |   96.49983   83.51518     1.16   0.270    -85.46412    278.4638
         gt1859 |   258.5153   493.2684     0.52   0.610    -816.2243    1333.255
         gt1957 |  -356.6561    1058.14    -0.34   0.742    -2662.145    1948.833
          _cons |  -411.8145   250.8606    -1.64   0.127    -958.3928    134.7637
----------------+----------------------------------------------------------------
        sigma_u |  3294.3571
        sigma_e |    1293.92
            rho |  .86635055   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil gt1789 gt1859 gt1957 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1445                         Obs per group: min =         5
       between = 0.0090                                        avg =      34.1
       overall = 0.1171                                        max =       109

                                                F(3,12)            =     11.99
corr(u_i, Xb)  = -0.1765                        Prob > F           =    0.0006

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
       mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gt1789 |   .0028945   .0024602     1.18   0.262    -.0024658    .0082548
      gt1859 |   .0207795   .0037301     5.57   0.000     .0126522    .0289067
      gt1957 |  -.0200939   .0051052    -3.94   0.002    -.0312172   -.0089706
       _cons |   .0138391   .0016176     8.56   0.000     .0103145    .0173636
-------------+----------------------------------------------------------------
     sigma_u |   .0220831
     sigma_e |  .02160798
         rho |  .51087316   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib gt1789 gt1859 gt1957 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1613                         Obs per group: min =         5
       between = 0.0137                                        avg =      34.1
       overall = 0.0358                                        max =       109

                                                F(5,12)            =      5.47
corr(u_i, Xb)  = -0.7650                        Prob > F           =    0.0075

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2258593   .1063515     2.12   0.055    -.0058607    .4575793
firstcruise_lib |  -.0130483   .0048225    -2.71   0.019    -.0235556   -.0025409
         gt1789 |    .003492    .002177     1.60   0.135    -.0012513    .0082354
         gt1859 |   .0115653   .0037642     3.07   0.010     .0033637    .0197668
         gt1957 |  -.0023273   .0045008    -0.52   0.614    -.0121337     .007479
          _cons |   .0097087   .0028431     3.41   0.005      .003514    .0159033
----------------+----------------------------------------------------------------
        sigma_u |  .03148727
        sigma_e |  .02144556
            rho |  .68311653   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. /** Rerun key specifications with gt1793 as alternative to gt1789 **/
> gen gt1793=0;

. replace gt1793=1 if year>=1793;
(1253 real changes made)

. xtreg military1 gt1793 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2267                         Obs per group: min =         5
       between = 0.6435                                        avg =      34.1
       overall = 0.3386                                        max =       109

                                                F(3,12)            =      9.89
corr(u_i, Xb)  = 0.2242                         Prob > F           =    0.0015

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
   military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gt1793 |  -23.94881   148.0311    -0.16   0.874    -346.4808    298.5832
      gt1859 |   2031.408    547.449     3.71   0.003     838.6188    3224.197
      gt1970 |  -1166.261   448.4544    -2.60   0.023    -2143.359   -189.1629
       _cons |   348.5853    146.702     2.38   0.035     28.94908    668.2215
-------------+----------------------------------------------------------------
     sigma_u |   792.3244
     sigma_e |  1416.1418
         rho |  .23840554   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib gt1793 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3578                         Obs per group: min =         5
       between = 0.4252                                        avg =      34.1
       overall = 0.2563                                        max =       109

                                                F(5,12)            =    771.04
corr(u_i, Xb)  = -0.9325                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   43730.91   11851.39     3.69   0.003     17908.94    69552.88
firstcruise_lib |  -426.8321   271.6796    -1.57   0.142    -1018.771    165.1069
         gt1793 |   107.7579   82.70039     1.30   0.217    -72.43078    287.9466
         gt1859 |   209.9551   481.0164     0.44   0.670    -838.0895        1258
         gt1970 |   353.5628   340.1791     1.04   0.319    -387.6238    1094.749
          _cons |  -428.5103    243.103    -1.76   0.103    -958.1862    101.1656
----------------+----------------------------------------------------------------
        sigma_u |  3362.4386
        sigma_e |  1293.5752
            rho |   .8710768   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil gt1793 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1412                         Obs per group: min =         5
       between = 0.0166                                        avg =      34.1
       overall = 0.1077                                        max =       109

                                                F(3,12)            =     11.72
corr(u_i, Xb)  = -0.2183                        Prob > F           =    0.0007

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
       mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gt1793 |   .0030893   .0026983     1.14   0.275    -.0027897    .0089683
      gt1859 |   .0206145   .0037835     5.45   0.000     .0123709    .0288581
      gt1970 |  -.0200981   .0059952    -3.35   0.006    -.0331606   -.0070356
       _cons |   .0135169   .0016794     8.05   0.000     .0098577    .0171761
-------------+----------------------------------------------------------------
     sigma_u |  .02260808
     sigma_e |  .02164931
         rho |  .52165349   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib gt1793 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1616                         Obs per group: min =         5
       between = 0.0138                                        avg =      34.1
       overall = 0.0359                                        max =       109

                                                F(5,12)            =     71.13
corr(u_i, Xb)  = -0.7656                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2248602   .1056899     2.13   0.055    -.0054182    .4551387
firstcruise_lib |    -.01328   .0026297    -5.05   0.000    -.0190095   -.0075504
         gt1793 |   .0037387   .0023577     1.59   0.139    -.0013983    .0088758
         gt1859 |   .0114353   .0039054     2.93   0.013     .0029261    .0199444
         gt1970 |  -.0027238   .0044044    -0.62   0.548    -.0123201    .0068725
          _cons |   .0096874   .0027813     3.48   0.005     .0036275    .0157474
----------------+----------------------------------------------------------------
        sigma_u |  .03153029
        sigma_e |  .02144202
            rho |  .68377871   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. /**Table 2 NO CLUSTER**/
> xi: reg military1  gt1789 gt1859 gt1970 i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 15,   427) =   20.72
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.4456
                                                       Root MSE      =  1416.1

--------------------------------------------------------------------------------
               |               Robust
     military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        gt1789 |  -23.92975   92.00598    -0.26   0.795    -204.7707    156.9112
        gt1859 |   2030.983   242.7152     8.37   0.000     1553.918    2508.049
        gt1970 |  -1166.186    414.147    -2.82   0.005    -1980.207   -352.1656
 _Icountryno_2 |   1763.507   514.7107     3.43   0.001     751.8251    2775.189
 _Icountryno_3 |  -75.32203     134.75    -0.56   0.576    -340.1779    189.5338
 _Icountryno_4 |  -402.8317   416.9139    -0.97   0.334    -1222.291    416.6272
 _Icountryno_5 |  -592.9349   455.5324    -1.30   0.194      -1488.3      302.43
 _Icountryno_6 |   12.17419   47.50188     0.26   0.798    -81.19242    105.5408
 _Icountryno_7 |   1111.721   370.1944     3.00   0.003     384.0906    1839.351
 _Icountryno_8 |    1325.84   402.4912     3.29   0.001     534.7293    2116.951
 _Icountryno_9 |   84.50753   63.35086     1.33   0.183    -40.01081    209.0259
_Icountryno_10 |   25.69286   51.60543     0.50   0.619    -75.73942    127.1251
_Icountryno_11 |   1705.324   678.5987     2.51   0.012     371.5142    3039.133
_Icountryno_12 |   73.32271   91.38141     0.80   0.423    -106.2907    252.9361
_Icountryno_13 |   91.69241   47.40379     1.93   0.054    -1.481408    184.8662
         _cons |   59.49247   46.89352     1.27   0.205     -32.6784    151.6633
--------------------------------------------------------------------------------

. xi: reg military1 RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 17,   425) =   45.58
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5395
                                                       Root MSE      =  1293.6

---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   43707.09   9871.867     4.43   0.000     24303.33    63110.86
firstcruise_lib |  -427.2783   780.7481    -0.55   0.584    -1961.887     1107.33
         gt1789 |   96.67412   64.77145     1.49   0.136    -30.63815    223.9864
         gt1859 |   219.1592    383.682     0.57   0.568    -534.9914    973.3098
         gt1970 |   353.2559   629.3709     0.56   0.575    -883.8112    1590.323
  _Icountryno_2 |   1665.149   327.4234     5.09   0.000     1021.578     2308.72
  _Icountryno_3 |  -83.14281   111.0249    -0.75   0.454    -301.3691    135.0834
  _Icountryno_4 |   336.8906   401.1931     0.84   0.402     -451.679     1125.46
  _Icountryno_5 |   134.1793   430.8969     0.31   0.756     -712.775    981.1335
  _Icountryno_6 |  -65.48157   34.39578    -1.90   0.058    -133.0886    2.125459
  _Icountryno_7 |   685.1556   303.4315     2.26   0.024     88.74228    1281.569
  _Icountryno_8 |   381.7877    323.877     1.18   0.239    -254.8123    1018.388
  _Icountryno_9 |   6.851763    54.2977     0.13   0.900    -99.87371    113.5772
 _Icountryno_10 |   -51.9629   39.89581    -1.30   0.193    -130.3806    26.45476
 _Icountryno_11 |  -11740.48   2828.007    -4.15   0.000     -17299.1   -6181.857
 _Icountryno_12 |  -31.41233   78.38336    -0.40   0.689    -185.4796     122.655
 _Icountryno_13 |   14.03665   34.25956     0.41   0.682    -53.30262    81.37592
          _cons |   137.1482   33.54659     4.09   0.000     71.21035    203.0861
---------------------------------------------------------------------------------

. xi: reg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 19,   423) =   33.43
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5985
                                                       Root MSE      =  1210.8

---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   35002.65   6755.726     5.18   0.000     21723.68    48281.63
firstcruise_lib |  -3689.954   986.0773    -3.74   0.000    -5628.176   -1751.733
         popul1 |   .0127968   .0031152     4.11   0.000     .0066735    .0189201
        gdppcip |    .306215   .0781283     3.92   0.000     .1526469    .4597831
   literacy_qrt |  -78.38179   179.1254    -0.44   0.662    -430.4684    273.7049
      democracy |  -630.8632   375.0545    -1.68   0.093    -1368.066    106.3394
           year |  -1.421403   1.836434    -0.77   0.439    -5.031076     2.18827
  _Icountryno_2 |  -5171.528   2177.864    -2.37   0.018    -9452.311   -890.7456
  _Icountryno_3 |   73.24839   108.4222     0.68   0.500     -139.865    286.3617
  _Icountryno_4 |   328.4606   360.2576     0.91   0.362    -379.6575    1036.579
  _Icountryno_5 |   134.6994   417.3195     0.32   0.747    -685.5788    954.9776
  _Icountryno_6 |  -118.7488   431.1839    -0.28   0.783    -966.2787    728.7811
  _Icountryno_7 |   691.6958   282.4326     2.45   0.015     136.5497    1246.842
  _Icountryno_8 |  -24.42093   271.0824    -0.09   0.928    -557.2573    508.4155
  _Icountryno_9 |  -14.49001   92.21337    -0.16   0.875    -195.7435    166.7635
 _Icountryno_10 |   173.4961   234.2151     0.74   0.459    -286.8742    633.8664
 _Icountryno_11 |  -11066.04   1868.306    -5.92   0.000    -14738.36    -7393.72
 _Icountryno_12 |   -49.7607    144.329    -0.34   0.730    -333.4521    233.9307
 _Icountryno_13 |  -123.3272   56.08532    -2.20   0.028    -233.5678   -13.08653
          _cons |   2216.818    2954.95     0.75   0.454    -3591.397    8025.032
---------------------------------------------------------------------------------

. xi: reg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend r
> ussiatrend spaintrend swedentrend usatrend uktrend ottotrend i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 31,   411) =   29.64
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.6158
                                                       Root MSE      =  1201.6

-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   31969.21    8015.02     3.99   0.000     16213.66    47724.76
    firstcruise_lib |  -3264.737   1156.856    -2.82   0.005     -5538.83   -990.6436
             popul1 |   .0228253     .01743     1.31   0.191    -.0114378    .0570883
            gdppcip |   .1975507    .118421     1.67   0.096    -.0352356     .430337
       literacy_qrt |  -92.40057   275.8751    -0.33   0.738    -634.7028    449.9017
          democracy |    -111.13   463.2328    -0.24   0.811    -1021.731    799.4711
austriahungarytrend |  -1.742852   1.771835    -0.98   0.326    -5.225842    1.740137
         chinatrend |  -203.1999   253.9793    -0.80   0.424    -702.4603    296.0605
        francetrend |  -2.012804   2.913882    -0.69   0.490    -7.740776    3.715167
         italytrend |   2.094299   14.66084     0.14   0.886    -26.72528    30.91387
         japantrend |   41.78844    28.9867     1.44   0.150    -15.19224    98.76912
   netherlandstrend |  -1.103995   .9608903    -1.15   0.251    -2.992868     .784878
       germanytrend |   4.515208   5.816387     0.78   0.438     -6.91837    15.94879
        russiatrend |  -10.13296   10.39309    -0.97   0.330    -30.56322    10.29729
         spaintrend |  -2.112706   .6039142    -3.50   0.001    -3.299851   -.9255596
        swedentrend |   2.654593   7.634328     0.35   0.728    -12.35261    17.66179
           usatrend |   2.916337   29.95804     0.10   0.922    -55.97376    61.80643
            uktrend |  -3.197277   1.851567    -1.73   0.085    -6.836999    .4424456
          ottotrend |   1.412044   .8716426     1.62   0.106    -.3013896    3.125478
      _Icountryno_2 |   382864.7     485915     0.79   0.431      -572324     1338053
      _Icountryno_3 |   439.5907   4835.787     0.09   0.928    -9066.371    9945.552
      _Icountryno_4 |  -6943.556    27115.5    -0.26   0.798    -60245.93    46358.82
      _Icountryno_5 |  -84136.88    55710.5    -1.51   0.132    -193649.9    25376.19
      _Icountryno_6 |  -977.7717   3690.199    -0.26   0.791    -8231.791    6276.248
      _Icountryno_7 |  -10829.88   10476.19    -1.03   0.302    -31423.48    9763.719
      _Icountryno_8 |   14882.74   18462.54     0.81   0.421    -21410.05    51175.53
      _Icountryno_9 |   600.1723   3181.961     0.19   0.850    -5654.775     6855.12
     _Icountryno_10 |  -7071.728   11299.71    -0.63   0.532    -29284.16     15140.7
     _Icountryno_11 |   -20068.3   58168.05    -0.35   0.730    -134412.3    94275.69
     _Icountryno_12 |   2642.694   3479.704     0.76   0.448    -4197.543    9482.931
     _Icountryno_13 |  -5610.464    3464.94    -1.62   0.106    -12421.68    1200.752
              _cons |   2766.699   2898.284     0.95   0.340     -2930.61    8464.008
-------------------------------------------------------------------------------------

. /**Table 3 NO CLUSTER**/
> xi: reg mobil  gt1789 gt1859 gt1970 i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 15,   427) =   28.46
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3002
                                                       Root MSE      =  .02165

--------------------------------------------------------------------------------
               |               Robust
         mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        gt1789 |   .0028946   .0011635     2.49   0.013     .0006077    .0051815
        gt1859 |     .02078   .0039556     5.25   0.000     .0130051    .0285549
        gt1970 |   -.020103   .0041868    -4.80   0.000    -.0283324   -.0118736
 _Icountryno_2 |  -.0231886   .0048504    -4.78   0.000    -.0327223   -.0136549
 _Icountryno_3 |   .0031643    .003068     1.03   0.303     -.002866    .0091947
 _Icountryno_4 |    .008141   .0099945     0.81   0.416    -.0115037    .0277856
 _Icountryno_5 |  -.0127509   .0067024    -1.90   0.058    -.0259248    .0004229
 _Icountryno_6 |   .0309507   .0040055     7.73   0.000     .0230778    .0388237
 _Icountryno_7 |   .0188797   .0044575     4.24   0.000     .0101183     .027641
 _Icountryno_8 |  -.0051196   .0032413    -1.58   0.115    -.0114904    .0012512
 _Icountryno_9 |   .0067733    .005207     1.30   0.194    -.0034613    .0170078
_Icountryno_10 |   .0667919   .0229249     2.91   0.004     .0217322    .1118515
_Icountryno_11 |   -.007015   .0060141    -1.17   0.244    -.0188359    .0048059
_Icountryno_12 |    .004349   .0018194     2.39   0.017     .0007729    .0079251
_Icountryno_13 |  -.0040967   .0009047    -4.53   0.000    -.0058749   -.0023185
         _cons |   .0102894   .0008536    12.05   0.000     .0086117    .0119671
--------------------------------------------------------------------------------

. xi: reg mobil RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 17,   425) =   28.74
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3167
                                                       Root MSE      =  .02144

---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2242763   .0721085     3.11   0.002     .0825426    .3660099
firstcruise_lib |   -.013293   .0055275    -2.40   0.017    -.0241576   -.0024285
         gt1789 |   .0034903   .0011989     2.91   0.004     .0011336    .0058469
         gt1859 |   .0116665   .0049488     2.36   0.019     .0019392    .0213937
         gt1970 |  -.0027335   .0046855    -0.58   0.560    -.0119431     .006476
  _Icountryno_2 |  -.0234051   .0039476    -5.93   0.000    -.0311643   -.0156458
  _Icountryno_3 |   .0031155   .0029974     1.04   0.299    -.0027761    .0090071
  _Icountryno_4 |   .0117884    .010027     1.18   0.240    -.0079203    .0314971
  _Icountryno_5 |  -.0091682   .0067708    -1.35   0.176    -.0224766    .0041402
  _Icountryno_6 |   .0305643   .0040003     7.64   0.000     .0227016    .0384271
  _Icountryno_7 |   .0166335   .0041965     3.96   0.000     .0083851    .0248819
  _Icountryno_8 |  -.0097458   .0033127    -2.94   0.003    -.0162572   -.0032344
  _Icountryno_9 |   .0063869    .005208     1.23   0.221    -.0038497    .0166235
 _Icountryno_10 |   .0664055   .0229762     2.89   0.004     .0212444    .1115666
 _Icountryno_11 |  -.0731276   .0209407    -3.49   0.001    -.1142878   -.0319674
 _Icountryno_12 |   .0038382    .001767     2.17   0.030      .000365    .0073114
 _Icountryno_13 |   -.004483   .0008395    -5.34   0.000    -.0061332   -.0028329
          _cons |   .0106758   .0007839    13.62   0.000      .009135    .0122165
---------------------------------------------------------------------------------

. xi: reg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy year i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 19,   423) =   23.58
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3417
                                                       Root MSE      =   .0211

---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2046159   .0665371     3.08   0.002     .0738313    .3354005
firstcruise_lib |  -.0310548   .0099276    -3.13   0.002    -.0505685   -.0115412
         popul2 |   .0348975   .0350953     0.99   0.321    -.0340853    .1038803
       gdppcip2 |   .0012345   .0010284     1.20   0.231    -.0007869    .0032559
   literacy_qrt |    .000637   .0030125     0.21   0.833    -.0052844    .0065584
      democracy |   .0130481   .0087761     1.49   0.138    -.0042021    .0302983
           year |   .0000169    .000023     0.73   0.463    -.0000283    .0000621
  _Icountryno_2 |  -.0322545   .0232637    -1.39   0.166    -.0779814    .0134724
  _Icountryno_3 |   .0008224   .0024835     0.33   0.741    -.0040591    .0057039
  _Icountryno_4 |   .0183228   .0096922     1.89   0.059    -.0007281    .0373737
  _Icountryno_5 |  -.0030594   .0066556    -0.46   0.646    -.0161416    .0100229
  _Icountryno_6 |   .0290161   .0074142     3.91   0.000     .0144428    .0435894
  _Icountryno_7 |   .0186473   .0048374     3.85   0.000      .009139    .0281557
  _Icountryno_8 |  -.0067231   .0038791    -1.73   0.084    -.0143479    .0009017
  _Icountryno_9 |   .0070156   .0055149     1.27   0.204    -.0038245    .0178556
 _Icountryno_10 |   .0665941   .0246109     2.71   0.007     .0182193     .114969
 _Icountryno_11 |  -.0824112   .0196318    -4.20   0.000    -.1209993   -.0438232
 _Icountryno_12 |   .0002883   .0028705     0.10   0.920    -.0053539    .0059305
 _Icountryno_13 |  -.0048486   .0011699    -4.14   0.000    -.0071481   -.0025491
          _cons |  -.0198801   .0369033    -0.54   0.590    -.0924168    .0526566
---------------------------------------------------------------------------------

. xi: reg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russ
> iatrend spaintrend swedentrend usatrend uktrend ottotrend i.countryno if waryear==1, robust;
i.countryno       _Icountryno_1-13    (naturally coded; _Icountryno_1 omitted)

Linear regression                                      Number of obs =     443
                                                       F( 31,   411) =   20.49
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3711
                                                       Root MSE      =  .02092

-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |    .297664   .0822598     3.62   0.000     .1359615    .4593665
    firstcruise_lib |  -.0296438   .0108805    -2.72   0.007    -.0510322   -.0082554
             popul2 |  -.1022848   .1576135    -0.65   0.517    -.4121138    .2075443
           gdppcip2 |   .0002829   .0013051     0.22   0.828    -.0022825    .0028484
       literacy_qrt |     .00187   .0029457     0.63   0.526    -.0039205    .0076604
          democracy |   .0136457   .0108078     1.26   0.207    -.0075997    .0348911
austriahungarytrend |   .0000191    .000023     0.83   0.407    -.0000261    .0000644
         chinatrend |   .0021678   .0022141     0.98   0.328    -.0021845      .00652
        francetrend |   .0000382   .0000368     1.04   0.299     -.000034    .0001105
         italytrend |   .0001261   .0003333     0.38   0.705     -.000529    .0007812
         japantrend |   .0009482   .0003706     2.56   0.011     .0002196    .0016767
   netherlandstrend |   .0002428    .000107     2.27   0.024     .0000325    .0004532
       germanytrend |   .0001159   .0000786     1.48   0.141    -.0000385    .0002704
        russiatrend |   8.49e-07   .0001026     0.01   0.993    -.0002008    .0002025
         spaintrend |  -.0002398   .0000689    -3.48   0.001    -.0003753   -.0001043
        swedentrend |  -.0002323   .0006667    -0.35   0.728    -.0015427    .0010782
           usatrend |    .000782   .0003573     2.19   0.029     .0000796    .0014844
            uktrend |   .0000256   .0000309     0.83   0.409    -.0000353    .0000864
          ottotrend |   .0000318   .0000199     1.60   0.111    -7.30e-06     .000071
      _Icountryno_2 |  -4.154048   4.234848    -0.98   0.327    -12.47871    4.170616
      _Icountryno_3 |  -.0335791   .0756415    -0.44   0.657    -.1822716    .1151134
      _Icountryno_4 |  -.1867889   .6387206    -0.29   0.770    -1.442356    1.068778
      _Icountryno_5 |   -1.79433   .7127815    -2.52   0.012    -3.195483   -.3931782
      _Icountryno_6 |  -.3442513   .1834061    -1.88   0.061    -.7047823    .0162797
      _Icountryno_7 |  -.1612842   .1461913    -1.10   0.271    -.4486602    .1260918
      _Icountryno_8 |   .0356113   .1840326     0.19   0.847    -.3261514     .397374
      _Icountryno_9 |   .4347971   .1230769     3.53   0.000     .1928583    .6767358
     _Icountryno_10 |   .4831831   1.132181     0.43   0.670    -1.742405    2.708771
     _Icountryno_11 |   -1.57725   .6974346    -2.26   0.024    -2.948234   -.2062663
     _Icountryno_12 |  -.0116383   .0677308    -0.17   0.864    -.1447802    .1215037
     _Icountryno_13 |  -.0247628   .0519187    -0.48   0.634    -.1268221    .0772966
              _cons |  -.0224148   .0387314    -0.58   0.563    -.0985511    .0537215
-------------------------------------------------------------------------------------

. /** Use RR measure normalized by area **/
> xtreg military1 RRkmip_area firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2548                         Obs per group: min =         5
       between = 0.3843                                        avg =      34.1
       overall = 0.2908                                        max =       109

                                                F(5,12)            =     26.09
corr(u_i, Xb)  = 0.1186                         Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
    RRkmip_area |   10920.66   9841.452     1.11   0.289    -10522.03    32363.34
firstcruise_lib |  -288.2362   619.3302    -0.47   0.650    -1637.641    1061.169
         gt1789 |  -101.6694   143.1319    -0.71   0.491     -413.527    210.1882
         gt1859 |   1156.257   1079.888     1.07   0.305    -1196.618    3509.132
         gt1970 |  -786.0472   618.1393    -1.27   0.228    -2132.857    560.7626
          _cons |   445.6836   184.8274     2.41   0.033     42.97932    848.3879
----------------+----------------------------------------------------------------
        sigma_u |  1012.8498
        sigma_e |  1393.5042
            rho |  .34567451   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip_area firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3759                         Obs per group: min =         5
       between = 0.5574                                        avg =      34.1
       overall = 0.3585                                        max =       109

                                                F(7,12)            =     30.20
corr(u_i, Xb)  = -0.6819                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
    RRkmip_area |   8381.127   4997.158     1.68   0.119    -2506.745       19269
firstcruise_lib |  -4307.011   603.7103    -7.13   0.000    -5622.383    -2991.64
         popul1 |   .0201115    .005524     3.64   0.003     .0080758    .0321472
        gdppcip |   .2396699   .0726863     3.30   0.006     .0813001    .3980397
   literacy_qrt |   234.8321   190.5804     1.23   0.241    -180.4068    650.0711
      democracy |  -494.5991   604.9073    -0.82   0.429    -1812.579    823.3808
           year |  -2.750388   .8749188    -3.14   0.008    -4.656672   -.8441034
          _cons |   3894.874   1244.342     3.13   0.009     1183.686    6606.063
----------------+----------------------------------------------------------------
        sigma_u |  2421.5608
        sigma_e |  1278.2322
            rho |  .78208673   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip_area firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend
>  russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4254                         Obs per group: min =         5
       between = 0.2878                                        avg =      34.1
       overall = 0.0280                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
        RRkmip_area |   4178.862   3463.052     1.21   0.251    -3366.481    11724.21
    firstcruise_lib |  -3547.705   1081.415    -3.28   0.007    -5903.907   -1191.503
             popul1 |   .0312467   .0236143     1.32   0.210    -.0202046    .0826979
            gdppcip |   .1717265   .1235889     1.39   0.190    -.0975505    .4410035
       literacy_qrt |   135.1625   204.0264     0.66   0.520    -309.3727    579.6978
          democracy |    176.238   271.3221     0.65   0.528     -414.922    767.3981
austriahungarytrend |  -4.884488    2.26978    -2.15   0.052    -9.829913    .0609375
         chinatrend |   -293.134   365.4763    -0.80   0.438    -1089.438    503.1703
        francetrend |  -2.005794   1.776281    -1.13   0.281    -5.875978     1.86439
         italytrend |  -4.816585   5.949735    -0.81   0.434    -17.77994    8.146775
         japantrend |    47.1239   13.38408     3.52   0.004     17.96249     76.2853
   netherlandstrend |  -.9250613   .9604982    -0.96   0.355    -3.017807    1.167684
       germanytrend |   6.493376   7.445722     0.87   0.400     -9.72946    22.71621
        russiatrend |  -3.767452    19.5801    -0.19   0.851    -46.42883    38.89393
         spaintrend |  -2.163768   .1429887   -15.13   0.000    -2.475314   -1.852222
        swedentrend |  -3.599492   5.629156    -0.64   0.535    -15.86437    8.665385
           usatrend |  -28.85895   43.35834    -0.67   0.518    -123.3287    65.61075
            uktrend |  -5.084663   1.976236    -2.57   0.024    -9.390512   -.7788139
          ottotrend |   1.768268   1.005404     1.76   0.104      -.42232    3.958855
              _cons |   12049.63   21177.86     0.57   0.580    -34092.95    58192.22
--------------------+----------------------------------------------------------------
            sigma_u |     157890
            sigma_e |  1244.2243
                rho |   .9999379   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip_area firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1797                         Obs per group: min =         5
       between = 0.0160                                        avg =      34.1
       overall = 0.1865                                        max =       109

                                                F(5,12)            =     28.06
corr(u_i, Xb)  = -0.0003                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
    RRkmip_area |   .1785603   .0245368     7.28   0.000     .1250993    .2320213
firstcruise_lib |  -.0113665   .0037756    -3.01   0.011    -.0195929   -.0031401
         gt1789 |   .0016096   .0020824     0.77   0.455    -.0029276    .0061468
         gt1859 |   .0065876   .0028641     2.30   0.040     .0003474    .0128279
         gt1970 |  -.0081496   .0049625    -1.64   0.126    -.0189619    .0026627
          _cons |   .0152008   .0019669     7.73   0.000     .0109153    .0194862
----------------+----------------------------------------------------------------
        sigma_u |   .0199149
        sigma_e |  .02120844
            rho |  .46857588   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip_area firstcruise_lib popul2 gdppcip2 literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1959                         Obs per group: min =         5
       between = 0.0662                                        avg =      34.1
       overall = 0.1429                                        max =       109

                                                F(7,12)            =    259.31
corr(u_i, Xb)  = -0.2027                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
    RRkmip_area |   .1276952    .043766     2.92   0.013     .0323372    .2230531
firstcruise_lib |  -.0276103   .0113047    -2.44   0.031    -.0522411   -.0029795
         popul2 |   .0630631    .036176     1.74   0.107    -.0157577    .1418839
       gdppcip2 |   .0003159   .0014374     0.22   0.830    -.0028159    .0034478
   literacy_qrt |    .001939   .0033456     0.58   0.573    -.0053505    .0092286
      democracy |   .0112971   .0052294     2.16   0.052    -.0000967     .022691
           year |  -6.75e-07   .0000136    -0.05   0.961    -.0000302    .0000289
          _cons |   .0108952   .0202237     0.54   0.600    -.0331686     .054959
----------------+----------------------------------------------------------------
        sigma_u |  .02437809
        sigma_e |  .02104834
            rho |  .57290815   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip_area firstcruise_lib popul2 gdppcip2 literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend ru
> ssiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2252                         Obs per group: min =         5
       between = 0.1617                                        avg =      34.1
       overall = 0.0039                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
        RRkmip_area |   .1704347    .082285     2.07   0.061    -.0088489    .3497184
    firstcruise_lib |  -.0253245   .0114799    -2.21   0.048     -.050337    -.000312
             popul2 |  -.1248153    .339526    -0.37   0.720    -.8645789    .6149483
           gdppcip2 |  -.0002389   .0014339    -0.17   0.870    -.0033631    .0028853
       literacy_qrt |   .0028955   .0049387     0.59   0.569     -.007865     .013656
          democracy |    .010485   .0040325     2.60   0.023      .001699    .0192711
austriahungarytrend |  -.0000201   .0000333    -0.60   0.557    -.0000928    .0000525
         chinatrend |   .0025867   .0047455     0.55   0.596    -.0077528    .0129261
        francetrend |   .0000446    .000041     1.09   0.298    -.0000448    .0001339
         italytrend |    .000044   .0001361     0.32   0.752    -.0002525    .0003405
         japantrend |   .0009071   .0002396     3.79   0.003     .0003851     .001429
   netherlandstrend |   .0002472   .0000119    20.70   0.000     .0002212    .0002732
       germanytrend |   .0000585   .0001218     0.48   0.640    -.0002069    .0003239
        russiatrend |   .0001614   .0002568     0.63   0.542    -.0003983     .000721
         spaintrend |  -.0002396   2.12e-06  -112.77   0.000    -.0002442    -.000235
        swedentrend |  -.0002602   .0001357    -1.92   0.079    -.0005559    .0000355
           usatrend |   .0006359   .0006463     0.98   0.345    -.0007722     .002044
            uktrend |  -6.92e-06   .0000338    -0.20   0.841    -.0000806    .0000668
          ottotrend |   .0000313   .0000136     2.31   0.040     1.77e-06    .0000609
              _cons |  -.2475989   .2779466    -0.89   0.391    -.8531926    .3579949
--------------------+----------------------------------------------------------------
            sigma_u |  1.4484222
            sigma_e |  .02095983
                rho |  .99979064   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 and 3 with nuclear cap**/
> xtreg military1 RRkmip1 nuclearcap gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3576                         Obs per group: min =         5
       between = 0.4257                                        avg =      34.1
       overall = 0.2564                                        max =       109

                                                F(5,12)            =    610.17
corr(u_i, Xb)  = -0.9327                        Prob > F           =    0.0000

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
   military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |   43847.89   11777.47     3.72   0.003     18186.98    69508.79
  nuclearcap |  -296.0655    584.916    -0.51   0.622    -1570.488     978.357
      gt1789 |   98.61746   84.18167     1.17   0.264    -84.79865    282.0336
      gt1859 |   223.9272   460.9035     0.49   0.636    -780.2953     1228.15
      gt1970 |   204.3438   356.9897     0.57   0.578      -573.47    982.1575
       _cons |  -429.8688   235.2933    -1.83   0.093    -942.5289    82.79122
-------------+----------------------------------------------------------------
     sigma_u |  3365.0002
     sigma_e |  1293.7993
         rho |  .87120889   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg military1 RRkmip1 nuclearcap popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4173                         Obs per group: min =         5
       between = 0.6451                                        avg =      34.1
       overall = 0.3043                                        max =       109

                                                F(7,12)            =    881.66
corr(u_i, Xb)  = -0.9381                        Prob > F           =    0.0000

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
   military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |   40909.69   5707.309     7.17   0.000     28474.53    53344.85
  nuclearcap |  -2269.164   290.9161    -7.80   0.000    -2903.016   -1635.313
      popul1 |   .0091585   .0027627     3.32   0.006      .003139     .015178
     gdppcip |   .2163848   .1035595     2.09   0.059     -.009252    .4420216
literacy_qrt |  -154.2562   110.5066    -1.40   0.188    -395.0295    86.51702
   democracy |   -434.446    443.372    -0.98   0.346    -1400.471    531.5787
        year |   .2384693   .9984091     0.24   0.815    -1.936877    2.413816
       _cons |  -1074.836    1686.86    -0.64   0.536    -4750.189    2600.518
-------------+----------------------------------------------------------------
     sigma_u |  3475.2796
     sigma_e |  1235.0905
         rho |  .88785954   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg military1 RRkmip1 nuclearcap popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiatr
> end spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4451                         Obs per group: min =         5
       between = 0.1555                                        avg =      34.1
       overall = 0.0011                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9995                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   37883.53   4424.237     8.56   0.000     28243.95    47523.12
         nuclearcap |  -1896.331   316.3437    -5.99   0.000    -2585.585   -1207.077
             popul1 |   .0162996   .0226505     0.72   0.486    -.0330516    .0656509
            gdppcip |   .1025756   .1210322     0.85   0.413    -.1611309     .366282
       literacy_qrt |  -107.2315   231.8304    -0.46   0.652    -612.3466    397.8836
          democracy |   48.39897   221.2038     0.22   0.830    -433.5628    530.3607
austriahungarytrend |  -.3841923   1.239701    -0.31   0.762    -3.085269    2.316885
         chinatrend |  -160.8789   327.6932    -0.49   0.632     -874.861    553.1031
        francetrend |  -1.635775   1.744682    -0.94   0.367     -5.43711    2.165561
         italytrend |   5.359658   4.745009     1.13   0.281    -4.978828    15.69814
         japantrend |   47.17301   13.37496     3.53   0.004     18.03148    76.31453
   netherlandstrend |  -.2966459    .937631    -0.32   0.757    -2.339568    1.746277
       germanytrend |   7.692044   6.411924     1.20   0.253     -6.27834    21.66243
        russiatrend |  -7.049045   16.06607    -0.44   0.669      -42.054    27.95591
         spaintrend |    -2.0665   .1367594   -15.11   0.000    -2.364473   -1.768527
        swedentrend |    3.12045   6.401083     0.49   0.635    -10.82631    17.06721
           usatrend |   14.43406   35.83038     0.40   0.694    -63.63362    92.50174
            uktrend |   -.563788   1.180113    -0.48   0.641    -3.135034    2.007458
          ottotrend |    1.22225   .9692655     1.26   0.231    -.8895981    3.334098
              _cons |  -441.6546   17649.02    -0.03   0.980    -38895.57    38012.26
--------------------+----------------------------------------------------------------
            sigma_u |  92376.192
            sigma_e |  1222.7894
                rho |  .99982481   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 nuclearcap gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1638                         Obs per group: min =         5
       between = 0.0137                                        avg =      34.1
       overall = 0.0373                                        max =       109

                                                F(5,12)            =      6.98
corr(u_i, Xb)  = -0.7626                        Prob > F           =    0.0028

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
       mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |    .230665   .1092325     2.11   0.056    -.0073323    .4686622
  nuclearcap |  -.0128785   .0069351    -1.86   0.088    -.0279888    .0022318
      gt1789 |   .0035645   .0021786     1.64   0.128    -.0011824    .0083113
      gt1859 |   .0119504   .0043427     2.75   0.018     .0024886    .0214123
      gt1970 |  -.0046395   .0031782    -1.46   0.170    -.0115642    .0022851
       _cons |   .0096345   .0028586     3.37   0.006     .0034061    .0158629
-------------+----------------------------------------------------------------
     sigma_u |  .03143254
     sigma_e |  .02141302
         rho |  .68302079   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg mobil RRkmip1 nuclearcap popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1966                         Obs per group: min =         5
       between = 0.0226                                        avg =      34.1
       overall = 0.0327                                        max =       109

                                                F(7,12)            =  10043.44
corr(u_i, Xb)  = -0.8048                        Prob > F           =    0.0000

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
       mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |   .2421937   .0776893     3.12   0.009     .0729233    .4114641
  nuclearcap |  -.0276044   .0086331    -3.20   0.008    -.0464144   -.0087945
      popul1 |   2.10e-08   3.60e-08     0.58   0.570    -5.75e-08    9.95e-08
     gdppcip |   9.49e-07   1.08e-06     0.88   0.395    -1.39e-06    3.29e-06
literacy_qrt |  -.0001243   .0033755    -0.04   0.971    -.0074788    .0072303
   democracy |   .0147745   .0035949     4.11   0.001     .0069418    .0226072
        year |    .000027   .0000165     1.64   0.128    -8.97e-06     .000063
       _cons |   -.038149   .0252681    -1.51   0.157    -.0932035    .0169055
-------------+----------------------------------------------------------------
     sigma_u |  .03512245
     sigma_e |  .02103843
         rho |  .73594137   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg mobil RRkmip1 nuclearcap popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiatrend 
> spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2355                         Obs per group: min =         5
       between = 0.1456                                        avg =      34.1
       overall = 0.0029                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |     .35731   .0972902     3.67   0.003     .1453329     .569287
         nuclearcap |   -.028647   .0064547    -4.44   0.001    -.0427106   -.0145833
             popul1 |  -1.60e-07   2.68e-07    -0.60   0.562    -7.44e-07    4.25e-07
            gdppcip |   1.19e-07   9.27e-07     0.13   0.900    -1.90e-06    2.14e-06
       literacy_qrt |   .0015426   .0054952     0.28   0.784    -.0104304    .0135156
          democracy |   .0142605   .0015757     9.05   0.000     .0108273    .0176937
austriahungarytrend |   .0000293   .0000175     1.68   0.120    -8.81e-06    .0000674
         chinatrend |   .0029297   .0037282     0.79   0.447    -.0051934    .0110529
        francetrend |   .0000384   .0000361     1.06   0.308    -.0000402    .0001169
         italytrend |   .0001458    .000141     1.03   0.322    -.0001615    .0004531
         japantrend |   .0009664    .000213     4.54   0.001     .0005023    .0014306
   netherlandstrend |   .0002444   7.78e-06    31.43   0.000     .0002275    .0002614
       germanytrend |   .0001277   .0000853     1.50   0.160    -.0000582    .0003136
        russiatrend |   .0000267   .0001843     0.15   0.887    -.0003748    .0004283
         spaintrend |  -.0002394   1.68e-06  -142.64   0.000     -.000243   -.0002357
        swedentrend |  -.0002231   .0001513    -1.48   0.166    -.0005527    .0001064
           usatrend |   .0009311   .0005525     1.69   0.118    -.0002727    .0021348
            uktrend |   .0000488   .0000129     3.77   0.003     .0000206     .000077
          ottotrend |   .0000297   .0000107     2.77   0.017     6.36e-06     .000053
              _cons |     -.3312   .2040592    -1.62   0.131    -.7758068    .1134068
--------------------+----------------------------------------------------------------
            sigma_u |  1.6403749
            sigma_e |   .0208204
                rho |  .99983893   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 and 3 with estwarheads **/
> xtreg military1 RRkmip1 estwarheads gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3571                         Obs per group: min =         5
       between = 0.4220                                        avg =      34.1
       overall = 0.2531                                        max =       109

                                                F(5,12)            = 375200.56
corr(u_i, Xb)  = -0.9352                        Prob > F           =    0.0000

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
   military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |   44068.36   12024.26     3.66   0.003     17869.76    70266.96
 estwarheads |    .007239   .0174964     0.41   0.686    -.0308824    .0453603
      gt1789 |   98.82465   84.22656     1.17   0.263    -84.68927    282.3386
      gt1859 |   199.4689   478.6829     0.42   0.684    -843.4914    1242.429
      gt1970 |  -53.38012   433.0966    -0.12   0.904    -997.0166    890.2564
       _cons |  -444.4158   257.6582    -1.72   0.110    -1005.805    116.9732
-------------+----------------------------------------------------------------
     sigma_u |  3445.0184
     sigma_e |  1294.3306
         rho |  .87630239   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg military1 RRkmip1 estwarheads popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3898                         Obs per group: min =         5
       between = 0.6117                                        avg =      34.1
       overall = 0.2927                                        max =       109

                                                F(7,12)            = 122954.60
corr(u_i, Xb)  = -0.9367                        Prob > F           =    0.0000

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
   military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |   41347.87   8825.158     4.69   0.001     22119.51    60576.24
 estwarheads |  -.0427883   .0365526    -1.17   0.264    -.1224297     .036853
      popul1 |   .0060942   .0047545     1.28   0.224     -.004265    .0164535
     gdppcip |   .1147951   .1504235     0.76   0.460    -.2129495    .4425397
literacy_qrt |   -117.679   147.3228    -0.80   0.440    -438.6678    203.3097
   democracy |  -493.3361   610.8661    -0.81   0.435    -1824.299    837.6267
        year |   1.087982   1.667025     0.65   0.526    -2.544153    4.720117
       _cons |  -2401.926   2772.236    -0.87   0.403     -8442.11    3638.258
-------------+----------------------------------------------------------------
     sigma_u |  3351.1141
     sigma_e |  1263.9412
         rho |   .8754593   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg military1 RRkmip1 estwarheads popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiat
> rend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4502                         Obs per group: min =         5
       between = 0.1823                                        avg =      34.1
       overall = 0.0042                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   32613.17   2657.637    12.27   0.000     26822.67    38403.66
        estwarheads |  -.1176682   .0120284    -9.78   0.000    -.1438758   -.0914606
             popul1 |    .024775   .0178256     1.39   0.190    -.0140636    .0636136
            gdppcip |  -.0326161   .0992123    -0.33   0.748     -.248781    .1835488
       literacy_qrt |  -96.82822   242.2523    -0.40   0.696    -624.6506    430.9941
          democracy |   261.1804   185.8196     1.41   0.185    -143.6857    666.0465
austriahungarytrend |  -.8600149   .7282866    -1.18   0.261    -2.446815    .7267854
         chinatrend |  -345.5477   250.7667    -1.38   0.193    -891.9214     200.826
        francetrend |  -.7894487   1.874466    -0.42   0.681     -4.87356    3.294662
         italytrend |   6.863095    5.84174     1.17   0.263    -5.864964    19.59115
         japantrend |   48.70754   11.09167     4.39   0.001     24.54087    72.87421
   netherlandstrend |   .7818504   .7793965     1.00   0.336    -.9163087    2.480009
       germanytrend |   8.646586   4.763795     1.82   0.095    -1.732832      19.026
        russiatrend |  -11.90458   12.14299    -0.98   0.346    -38.36188    14.55272
         spaintrend |  -2.111585   .1081904   -19.52   0.000    -2.347312   -1.875858
        swedentrend |   2.915224   6.683443     0.44   0.670    -11.64675     17.4772
           usatrend |   39.64812   25.91845     1.53   0.152    -16.82334    96.11958
            uktrend |  -1.062126   1.042833    -1.02   0.329    -3.334264    1.210013
          ottotrend |   1.662659   .7565613     2.20   0.048     .0142537    3.311065
              _cons |   2997.043   12491.36     0.24   0.814    -24219.29    30213.38
--------------------+----------------------------------------------------------------
            sigma_u |  191290.89
            sigma_e |  1217.1438
                rho |  .99995952   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 estwarheads gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1576                         Obs per group: min =         5
       between = 0.0145                                        avg =      34.1
       overall = 0.0346                                        max =       109

                                                F(5,12)            =  40809.72
corr(u_i, Xb)  = -0.7650                        Prob > F           =    0.0000

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
       mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |   .2169279   .1148392     1.89   0.083    -.0332853     .467141
 estwarheads |  -1.26e-07   1.93e-07    -0.66   0.525    -5.47e-07    2.94e-07
      gt1789 |   .0034931   .0021783     1.60   0.135    -.0012531    .0082394
      gt1859 |   .0117103   .0036377     3.22   0.007     .0037845    .0196361
      gt1970 |  -.0135574   .0084597    -1.60   0.135    -.0319895    .0048748
       _cons |   .0097299   .0031451     3.09   0.009     .0028773    .0165825
-------------+----------------------------------------------------------------
     sigma_u |   .0314529
     sigma_e |  .02149236
         rho |  .68169825   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg mobil RRkmip1 estwarheads popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1735                         Obs per group: min =         5
       between = 0.0037                                        avg =      34.1
       overall = 0.0263                                        max =       109

                                                F(7,12)            =  66390.56
corr(u_i, Xb)  = -0.8354                        Prob > F           =    0.0000

                             (Std. Err. adjusted for 13 clusters in countryno)
------------------------------------------------------------------------------
             |               Robust
       mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     RRkmip1 |   .2752518   .1135523     2.42   0.032     .0278427     .522661
 estwarheads |  -9.66e-08   4.67e-07    -0.21   0.839    -1.11e-06    9.21e-07
      popul1 |  -3.02e-08   2.60e-08    -1.16   0.269    -8.69e-08    2.66e-08
     gdppcip |  -5.23e-07   1.59e-06    -0.33   0.748    -3.99e-06    2.95e-06
literacy_qrt |   .0002825   .0035508     0.08   0.938    -.0074539     .008019
   democracy |   .0144476   .0049107     2.94   0.012     .0037481    .0251471
        year |   .0000391   .0000226     1.73   0.110    -.0000102    .0000884
       _cons |  -.0572536   .0355505    -1.61   0.133    -.1347115    .0202042
-------------+----------------------------------------------------------------
     sigma_u |  .03581692
     sigma_e |  .02133897
         rho |  .73803328   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg mobil RRkmip1 estwarheads popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiatrend
>  spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2182                         Obs per group: min =         5
       between = 0.1077                                        avg =      34.1
       overall = 0.0001                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9997                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .3132396   .1278896     2.45   0.031     .0345921    .5918871
        estwarheads |  -8.01e-07   1.83e-07    -4.38   0.001    -1.20e-06   -4.02e-07
             popul1 |  -1.04e-07   2.85e-07    -0.37   0.720    -7.25e-07    5.16e-07
            gdppcip |  -1.76e-06   8.82e-07    -2.00   0.069    -3.69e-06    1.59e-07
       literacy_qrt |   .0018788   .0058704     0.32   0.754    -.0109118    .0146693
          democracy |   .0168572   .0026506     6.36   0.000      .011082    .0226325
austriahungarytrend |    .000029   .0000205     1.42   0.182    -.0000157    .0000737
         chinatrend |   .0011523   .0039515     0.29   0.776    -.0074574     .009762
        francetrend |   .0000487   .0000414     1.17   0.263    -.0000416     .000139
         italytrend |   .0001698   .0001599     1.06   0.309    -.0001786    .0005182
         japantrend |    .001019   .0002131     4.78   0.000     .0005546    .0014834
   netherlandstrend |   .0002597   7.47e-06    34.78   0.000     .0002434     .000276
       germanytrend |   .0001577   .0000817     1.93   0.078    -.0000204    .0003358
        russiatrend |  -3.41e-06   .0001832    -0.02   0.985    -.0004025    .0003957
         spaintrend |  -.0002396   1.78e-06  -134.43   0.000    -.0002435   -.0002357
        swedentrend |  -.0002313   .0001617    -1.43   0.178    -.0005837    .0001211
           usatrend |   .0010415   .0005627     1.85   0.089    -.0001845    .0022675
            uktrend |   .0000463   .0000197     2.35   0.037     3.31e-06    .0000894
          ottotrend |   .0000333   .0000113     2.94   0.012     8.60e-06     .000058
              _cons |  -.2947304   .2088365    -1.41   0.184    -.7497461    .1602852
--------------------+----------------------------------------------------------------
            sigma_u |  .93255475
            sigma_e |  .02105439
                rho |  .99949053   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 and 3 with census as alternative measure of fiscal capacity**/
> xtreg military1 RRkmip1 firstcruise_lib popul1 census literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       331
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.4727                         Obs per group: min =         5
       between = 0.8649                                        avg =      30.1
       overall = 0.5241                                        max =       109

                                                F(7,10)            =  1.04e+06
corr(u_i, Xb)  = -0.5592                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   50357.34   7864.756     6.40   0.000     32833.58    67881.11
firstcruise_lib |  -1416.995    224.851    -6.30   0.000    -1917.994   -915.9961
         popul1 |   .0061978   .0020491     3.02   0.013     .0016322    .0107634
         census |  -270.8185   291.9866    -0.93   0.376    -921.4052    379.7681
   literacy_qrt |  -212.4913   129.5209    -1.64   0.132    -501.0819    76.09928
      democracy |  -113.5329   242.3722    -0.47   0.650    -653.5717    426.5059
           year |   3.377144   2.580558     1.31   0.220    -2.372697    9.126985
          _cons |  -5425.695    4327.26    -1.25   0.238    -15067.43    4216.041
----------------+----------------------------------------------------------------
        sigma_u |  971.22689
        sigma_e |  1214.7485
            rho |  .38996377   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 census literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russ
> iatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);
note: austriahungarytrend omitted because of collinearity
note: usatrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       331
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.5182                         Obs per group: min =         5
       between = 0.4301                                        avg =      30.1
       overall = 0.0365                                        max =       109

                                                F(6,10)            =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                                    (Std. Err. adjusted for 11 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   30070.69   5274.413     5.70   0.000     18318.57    41822.82
    firstcruise_lib |  -1438.501   80.97935   -17.76   0.000    -1618.935   -1258.068
             popul1 |   .0350141    .012952     2.70   0.022     .0061554    .0638729
             census |   39.30999   83.76602     0.47   0.649    -147.3323    225.9523
       literacy_qrt |  -176.7415   241.9953    -0.73   0.482    -715.9406    362.4576
          democracy |   246.5229   92.19407     2.67   0.023     41.10171    451.9441
austriahungarytrend |          0  (omitted)
         chinatrend |  -440.5182   177.2619    -2.49   0.032    -835.4824   -45.55399
        francetrend |  -.3927281   1.669737    -0.24   0.819    -4.113135    3.327678
         italytrend |   7.078733   7.069305     1.00   0.340     -8.67266    22.83013
         japantrend |   41.24998   7.786375     5.30   0.000     23.90085    58.59911
   netherlandstrend |   .4727525   .0515613     9.17   0.000     .3578667    .5876383
       germanytrend |   4.812448   2.582854     1.86   0.092    -.9425085    10.56741
        russiatrend |  -18.56566   7.171517    -2.59   0.027    -34.54479   -2.586522
         spaintrend |  -2.177365    .080826   -26.94   0.000    -2.357456   -1.997273
        swedentrend |   5.097212   6.667152     0.76   0.462    -9.758129    19.95255
           usatrend |          0  (omitted)
            uktrend |  -1.945577   .7043323    -2.76   0.020    -3.514927   -.3762266
          ottotrend |   2.047762   .5180782     3.95   0.003     .8934115    3.202112
              _cons |   16988.85   9016.524     1.88   0.089    -3101.214    37078.92
--------------------+----------------------------------------------------------------
            sigma_u |  257551.57
            sigma_e |   1180.143
                rho |    .999979   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 census literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       331
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.1963                         Obs per group: min =         5
       between = 0.0129                                        avg =      30.1
       overall = 0.1305                                        max =       109

                                                F(7,10)            =   6762.72
corr(u_i, Xb)  = -0.1665                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .3154393   .1591974     1.98   0.076    -.0392745    .6701531
firstcruise_lib |  -.0281414   .0046244    -6.09   0.000    -.0384452   -.0178376
         popul2 |  -.0089268   .0667506    -0.13   0.896    -.1576565    .1398028
         census |  -.0022137   .0015171    -1.46   0.175     -.005594    .0011666
   literacy_qrt |    .000471   .0045134     0.10   0.919    -.0095855    .0105276
      democracy |   .0149203   .0031496     4.74   0.001     .0079027     .021938
           year |   .0000359   .0000318     1.13   0.284    -.0000348    .0001067
          _cons |  -.0467297   .0477069    -0.98   0.350    -.1530272    .0595678
----------------+----------------------------------------------------------------
        sigma_u |  .02268466
        sigma_e |  .02357965
            rho |  .48066214   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 census literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiatr
> end spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);
note: austriahungarytrend omitted because of collinearity
note: usatrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       331
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.2312                         Obs per group: min =         5
       between = 0.1574                                        avg =      30.1
       overall = 0.0081                                        max =       109

                                                F(6,10)            =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                                    (Std. Err. adjusted for 11 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .5728896   .2460374     2.33   0.042     .0246841    1.121095
    firstcruise_lib |  -.0278525   .0023955   -11.63   0.000      -.03319   -.0225149
             popul2 |     -.2332   .3590792    -0.65   0.531    -1.033278    .5668785
             census |   .0008025   .0022052     0.36   0.723     -.004111    .0057161
       literacy_qrt |   -.000625   .0060883    -0.10   0.920    -.0141906    .0129406
          democracy |   .0109052   .0032863     3.32   0.008     .0035828    .0182276
austriahungarytrend |          0  (omitted)
         chinatrend |   .0038216   .0048263     0.79   0.447    -.0069321    .0145754
        francetrend |   .0000464   .0000509     0.91   0.383    -.0000669    .0001598
         italytrend |   .0002086   .0001778     1.17   0.268    -.0001876    .0006048
         japantrend |   .0009161   .0002075     4.41   0.001     .0004537    .0013786
   netherlandstrend |   .0002457   1.43e-06   171.88   0.000     .0002425    .0002489
       germanytrend |   .0001052    .000079     1.33   0.213    -.0000708    .0002813
        russiatrend |   4.81e-06   .0001841     0.03   0.980    -.0004054     .000415
         spaintrend |  -.0002389   2.24e-06  -106.62   0.000    -.0002439   -.0002339
        swedentrend |  -.0001633   .0001677    -0.97   0.353    -.0005371    .0002104
           usatrend |          0  (omitted)
            uktrend |   .0000498   .0000148     3.36   0.007     .0000167    .0000829
          ottotrend |   .0000268   .0000144     1.87   0.091    -5.18e-06    .0000588
              _cons |  -.3180321   .2358854    -1.35   0.207    -.8436177    .2075534
--------------------+----------------------------------------------------------------
            sigma_u |  2.2239954
            sigma_e |  .02343886
                rho |  .99988894   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Use alternative measures of democracy **/
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt taxes year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4349                         Obs per group: min =         5
       between = 0.6871                                        avg =      34.1
       overall = 0.3197                                        max =       109

                                                F(7,12)            =    303.27
corr(u_i, Xb)  = -0.9254                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   32839.26   5198.127     6.32   0.000     21513.51       44165
firstcruise_lib |  -3623.448   673.9627    -5.38   0.000    -5091.886   -2155.009
         popul1 |    .014432   .0033083     4.36   0.001     .0072238    .0216402
        gdppcip |    .268402   .1051609     2.55   0.025      .039276     .497528
   literacy_qrt |  -109.5422   116.2534    -0.94   0.365    -362.8365    143.7521
          taxes |     196.39   114.4032     1.72   0.112    -52.87312    445.6531
           year |  -2.176182   1.731025    -1.26   0.233    -5.947761    1.595397
          _cons |   2849.516   2860.382     1.00   0.339    -3382.722    9081.754
----------------+----------------------------------------------------------------
        sigma_u |  3341.8494
        sigma_e |  1216.3191
            rho |   .8830247   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt taxes austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiat
> rend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4657                         Obs per group: min =         5
       between = 0.2151                                        avg =      34.1
       overall = 0.0088                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   31580.46   1784.258    17.70   0.000      27692.9    35468.03
    firstcruise_lib |  -3281.047   936.3611    -3.50   0.004    -5321.202   -1240.891
             popul1 |   .0226608   .0166553     1.36   0.199    -.0136279    .0589495
            gdppcip |    .203477   .1450848     1.40   0.186    -.1126358    .5195897
       literacy_qrt |  -107.2407   199.3267    -0.54   0.600    -541.5362    327.0548
              taxes |   348.3742   197.0366     1.77   0.102    -80.93157      777.68
austriahungarytrend |  -1.083266   1.017587    -1.06   0.308    -3.300398    1.133867
         chinatrend |  -199.3905   257.8456    -0.77   0.454    -761.1878    362.4068
        francetrend |  -3.752149    2.51007    -1.49   0.161    -9.221122    1.716824
         italytrend |   9.487092    5.25098     1.81   0.096    -1.953811      20.928
         japantrend |   41.88168   11.18972     3.74   0.003     17.50138    66.26199
   netherlandstrend |  -1.152096   1.162304    -0.99   0.341    -3.684539    1.380347
       germanytrend |   3.999635   5.399872     0.74   0.473    -7.765677    15.76495
        russiatrend |  -9.614667   12.90352    -0.75   0.471    -37.72901    18.49968
         spaintrend |   1.856799   2.278617     0.81   0.431    -3.107881    6.821479
        swedentrend |   3.059885   5.492148     0.56   0.588    -8.906479    15.02625
           usatrend |   2.070848   29.65899     0.07   0.945    -62.55054    66.69224
            uktrend |  -3.580413   2.253307    -1.59   0.138    -8.489948    1.329121
          ottotrend |   1.401019   .7261548     1.93   0.078    -.1811358    2.983175
              _cons |   4820.278   13782.76     0.35   0.733    -25209.78    34850.34
--------------------+----------------------------------------------------------------
            sigma_u |  109938.61
            sigma_e |  1199.8805
                rho |   .9998809   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt taxes year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1926                         Obs per group: min =         5
       between = 0.0171                                        avg =      34.1
       overall = 0.0299                                        max =       109

                                                F(7,12)            =    280.29
corr(u_i, Xb)  = -0.8002                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2206284   .0547451     4.03   0.002     .1013491    .3399076
firstcruise_lib |  -.0358899   .0095325    -3.77   0.003    -.0566593   -.0151204
         popul2 |   .0248458   .0510632     0.49   0.635    -.0864114    .1361029
       gdppcip2 |   .0022278   .0010043     2.22   0.047     .0000397    .0044159
   literacy_qrt |   .0008283   .0032132     0.26   0.801    -.0061726    .0078292
          taxes |   .0100825   .0023344     4.32   0.001     .0049962    .0151688
           year |   .0000184   .0000202     0.91   0.382    -.0000257    .0000624
          _cons |  -.0323656   .0311562    -1.04   0.319    -.1002493     .035518
----------------+----------------------------------------------------------------
        sigma_u |   .0348467
        sigma_e |  .02109134
            rho |  .73188197   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt taxes austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiatren
> d spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2249                         Obs per group: min =         5
       between = 0.1490                                        avg =      34.1
       overall = 0.0029                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .3529995   .1368746     2.58   0.024     .0547753    .6512237
    firstcruise_lib |  -.0343368   .0095431    -3.60   0.004    -.0551295   -.0135441
             popul2 |  -.1259417   .2867991    -0.44   0.668    -.7508233    .4989399
           gdppcip2 |   .0014122   .0012959     1.09   0.297    -.0014114    .0042357
       literacy_qrt |   .0021294   .0057963     0.37   0.720    -.0104996    .0147584
              taxes |   .0095039   .0055349     1.72   0.112    -.0025556    .0215634
austriahungarytrend |   .0000248   .0000266     0.93   0.369    -.0000331    .0000827
         chinatrend |      .0026    .003799     0.68   0.507    -.0056773    .0108774
        francetrend |   .0000146   .0000387     0.38   0.713    -.0000697    .0000988
         italytrend |   .0002697   .0002298     1.17   0.263    -.0002309    .0007703
         japantrend |   .0008951    .000215     4.16   0.001     .0004267    .0013634
   netherlandstrend |   .0002337   .0000113    20.68   0.000      .000209    .0002583
       germanytrend |   .0000565   .0000869     0.65   0.528     -.000133    .0002459
        russiatrend |  -.0000172   .0001665    -0.10   0.919      -.00038    .0003456
         spaintrend |  -.0001314   .0000621    -2.11   0.056    -.0002668    3.97e-06
        swedentrend |  -.0002401   .0001594    -1.51   0.158    -.0005873    .0001072
           usatrend |   .0007331   .0006952     1.05   0.312    -.0007816    .0022477
            uktrend |   .0000476    .000028     1.70   0.115    -.0000134    .0001086
          ottotrend |   .0000301    .000011     2.73   0.018     6.10e-06     .000054
              _cons |  -.2867173   .2201463    -1.30   0.217    -.7663749    .1929403
--------------------+----------------------------------------------------------------
            sigma_u |  1.4527207
            sigma_e |  .02096471
                rho |  .99979178   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt spending year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4355                         Obs per group: min =         5
       between = 0.6818                                        avg =      34.1
       overall = 0.3173                                        max =       109

                                                F(7,12)            =    219.21
corr(u_i, Xb)  = -0.9278                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   33365.76   5219.526     6.39   0.000     21993.39    44738.13
firstcruise_lib |  -3648.923   674.6375    -5.41   0.000    -5118.832   -2179.014
         popul1 |   .0145139   .0032969     4.40   0.001     .0073305    .0216972
        gdppcip |   .2755523   .1077861     2.56   0.025     .0407067     .510398
   literacy_qrt |  -124.3664   117.3751    -1.06   0.310    -380.1047    131.3719
       spending |   275.2265    160.348     1.72   0.112    -74.14168    624.5947
           year |  -2.552981   1.890003    -1.35   0.202    -6.670943    1.564981
          _cons |   3526.005    3120.86     1.13   0.281    -3273.764    10325.77
----------------+----------------------------------------------------------------
        sigma_u |  3398.0246
        sigma_e |  1215.6468
            rho |  .88653598   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt spending austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russ
> iatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4651                         Obs per group: min =         5
       between = 0.2077                                        avg =      34.1
       overall = 0.0074                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   31707.23   1787.447    17.74   0.000     27812.72    35601.74
    firstcruise_lib |  -3267.553   939.4531    -3.48   0.005    -5314.446    -1220.66
             popul1 |   .0224299   .0167785     1.34   0.206    -.0141273    .0589872
            gdppcip |   .2018858   .1468132     1.38   0.194    -.1179928    .5217644
       literacy_qrt |  -118.7053   198.9913    -0.60   0.562    -552.2701    314.8596
           spending |    286.804   215.6008     1.33   0.208    -182.9497    756.5578
austriahungarytrend |  -2.019147   .8661766    -2.33   0.038    -3.906384   -.1319101
         chinatrend |  -196.1804   260.4385    -0.75   0.466     -763.627    371.2663
        francetrend |  -3.327494   2.525176    -1.32   0.212    -8.829379    2.174391
         italytrend |   8.819253   5.515481     1.60   0.136    -3.197948    20.83645
         japantrend |   42.04706   11.21902     3.75   0.003     17.60291    66.49121
   netherlandstrend |  -1.138086   1.175464    -0.97   0.352    -3.699201    1.423029
       germanytrend |   4.354018   5.447715     0.80   0.440    -7.515533    16.22357
        russiatrend |  -9.309518   13.13306    -0.71   0.492    -37.92399    19.30496
         spaintrend |  -2.110489   .1006828   -20.96   0.000    -2.329858    -1.89112
        swedentrend |   3.376705   5.479647     0.62   0.549     -8.56242    15.31583
           usatrend |   2.709337   29.67567     0.09   0.929    -61.94839    67.36706
            uktrend |  -3.510032   2.266387    -1.55   0.147    -8.448066    1.428001
          ottotrend |    1.39298   .7330339     1.90   0.082    -.2041639    2.990123
              _cons |   4931.699    13872.9     0.36   0.728    -25294.75    35158.14
--------------------+----------------------------------------------------------------
            sigma_u |   108183.1
            sigma_e |  1200.4904
                rho |  .99987688   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt spending year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1882                         Obs per group: min =         5
       between = 0.0079                                        avg =      34.1
       overall = 0.0321                                        max =       109

                                                F(7,12)            =     50.95
corr(u_i, Xb)  = -0.8301                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2453296   .0568022     4.32   0.001     .1215683     .369091
firstcruise_lib |  -.0358557   .0097311    -3.68   0.003    -.0570579   -.0146535
         popul2 |   .0215311   .0525391     0.41   0.689    -.0929418    .1360039
       gdppcip2 |   .0024108   .0011343     2.13   0.055    -.0000607    .0048823
   literacy_qrt |   .0004528     .00357     0.13   0.901    -.0073256    .0082312
       spending |    .009105   .0030444     2.99   0.011     .0024718    .0157383
           year |   9.47e-06   .0000179     0.53   0.607    -.0000296    .0000486
          _cons |  -.0140609   .0276553    -0.51   0.620    -.0743167     .046195
----------------+----------------------------------------------------------------
        sigma_u |  .03607144
        sigma_e |  .02114803
            rho |  .74419911   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt spending austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiat
> rend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2230                         Obs per group: min =         5
       between = 0.1407                                        avg =      34.1
       overall = 0.0024                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .3565078   .1380599     2.58   0.024     .0557012    .6573144
    firstcruise_lib |  -.0339774   .0095813    -3.55   0.004    -.0548533   -.0131015
             popul2 |  -.1323859   .2820244    -0.47   0.647    -.7468643    .4820925
           gdppcip2 |   .0013718   .0013324     1.03   0.324    -.0015312    .0042748
       literacy_qrt |   .0018105   .0060008     0.30   0.768    -.0112641     .014885
           spending |   .0079048   .0055604     1.42   0.181    -.0042102    .0200199
austriahungarytrend |  -8.49e-07   .0000221    -0.04   0.970     -.000049    .0000473
         chinatrend |   .0026902   .0037342     0.72   0.485    -.0054458    .0108262
        francetrend |   .0000258   .0000382     0.68   0.511    -.0000573    .0001089
         italytrend |   .0002532   .0002442     1.04   0.320    -.0002788    .0007852
         japantrend |   .0008995   .0002141     4.20   0.001      .000433    .0013661
   netherlandstrend |    .000234   .0000116    20.21   0.000     .0002088    .0002592
       germanytrend |    .000066   .0000856     0.77   0.456    -.0001205    .0002525
        russiatrend |  -8.73e-06    .000164    -0.05   0.958    -.0003661    .0003487
         spaintrend |  -.0002396   1.80e-06  -133.06   0.000    -.0002436   -.0002357
        swedentrend |  -.0002313    .000165    -1.40   0.186    -.0005907    .0001282
           usatrend |   .0007504   .0006886     1.09   0.297      -.00075    .0022507
            uktrend |   .0000495    .000029     1.70   0.114    -.0000138    .0001128
          ottotrend |   .0000298   .0000108     2.76   0.017     6.30e-06    .0000534
              _cons |  -.2837392   .2203041    -1.29   0.222    -.7637406    .1962622
--------------------+----------------------------------------------------------------
            sigma_u |  1.5074196
            sigma_e |  .02098953
                rho |  .99980616   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /* Nationalism and RR interaction */
> 
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt litxRR democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4445                         Obs per group: min =         5
       between = 0.6977                                        avg =      34.1
       overall = 0.3222                                        max =       109

                                                F(8,12)            =    536.92
corr(u_i, Xb)  = -0.9346                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   7175.156   6879.304     1.04   0.318    -7813.559    22163.87
firstcruise_lib |  -3779.598   588.9919    -6.42   0.000    -5062.901   -2496.295
         popul1 |   .0143472   .0028336     5.06   0.000     .0081733    .0205212
        gdppcip |   .2984262   .1273409     2.34   0.037     .0209741    .5758782
   literacy_qrt |  -191.0323   177.9047    -1.07   0.304    -578.6534    196.5888
         litxRR |    7280.81   2176.586     3.35   0.006     2538.437    12023.18
      democracy |   -631.608   543.4091    -1.16   0.268    -1815.595    552.3788
           year |  -.3767978   1.802137    -0.21   0.838    -4.303316    3.549721
          _cons |  -100.7865   2919.756    -0.03   0.973    -6462.388    6260.815
----------------+----------------------------------------------------------------
        sigma_u |  3537.6341
        sigma_e |  1207.3549
            rho |  .89567369   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt litxRR democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytr
> end russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4678                         Obs per group: min =         5
       between = 0.2425                                        avg =      34.1
       overall = 0.0159                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9997                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   3338.566   11468.07     0.29   0.776    -21648.22    28325.35
    firstcruise_lib |  -3386.198   948.0338    -3.57   0.004    -5451.786   -1320.609
             popul1 |   .0271037   .0197868     1.37   0.196     -.016008    .0702153
            gdppcip |   .1913549   .1628788     1.17   0.263    -.1635274    .5462373
       literacy_qrt |  -243.1557   350.9395    -0.69   0.502    -1007.787    521.4758
             litxRR |   7235.591   3146.731     2.30   0.040     379.4538    14091.73
          democracy |  -92.53748   377.2764    -0.25   0.810    -914.5521    729.4771
austriahungarytrend |  -.7899746   .8975083    -0.88   0.396    -2.745477    1.165528
         chinatrend |  -247.8329   291.6384    -0.85   0.412    -883.2583    387.5925
        francetrend |  -.4471811   2.984927    -0.15   0.883    -6.950778    6.056416
         italytrend |   4.607692   8.585171     0.54   0.601    -14.09779    23.31317
         japantrend |   38.72687   13.70217     2.83   0.015     8.872397    68.58133
   netherlandstrend |  -1.070053   1.302422    -0.82   0.427    -3.907788    1.767681
       germanytrend |   4.073812   5.491657     0.74   0.472    -7.891481     16.0391
        russiatrend |  -9.427338   12.57068    -0.75   0.468    -36.81649    17.96181
         spaintrend |  -2.139047   .1190554   -17.97   0.000    -2.398446   -1.879648
        swedentrend |    6.81176   9.688367     0.70   0.495    -14.29738     27.9209
           usatrend |  -2.116841   32.38336    -0.07   0.949    -72.67411    68.44043
            uktrend |   -2.48395   1.449338    -1.71   0.112    -5.641787    .6738874
          ottotrend |   1.587827   .8590905     1.85   0.089      -.28397    3.459625
              _cons |   6002.684   13721.82     0.44   0.670    -23894.59    35899.96
--------------------+----------------------------------------------------------------
            sigma_u |   134319.4
            sigma_e |  1198.9527
                rho |  .99992033   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt litxRR democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1968                         Obs per group: min =         5
       between = 0.0469                                        avg =      34.1
       overall = 0.0271                                        max =       109

                                                F(8,12)            =   1631.34
corr(u_i, Xb)  = -0.8159                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |  -.2064569   .1323139    -1.56   0.145    -.4947441    .0818303
firstcruise_lib |  -.0323791   .0086685    -3.74   0.003     -.051266   -.0134921
         popul1 |   5.78e-08   3.82e-08     1.51   0.156    -2.54e-08    1.41e-07
        gdppcip |   1.12e-06   1.47e-06     0.76   0.460    -2.07e-06    4.31e-06
   literacy_qrt |  -.0010271   .0039046    -0.26   0.797    -.0095346    .0074804
         litxRR |   .1075534   .0433529     2.48   0.029     .0130957    .2020112
      democracy |   .0130371   .0046143     2.83   0.015     .0029833    .0230908
           year |   .0000323   .0000252     1.28   0.224    -.0000226    .0000873
          _cons |  -.0466688   .0391861    -1.19   0.257     -.132048    .0387104
----------------+----------------------------------------------------------------
        sigma_u |  .03721061
        sigma_e |  .02106119
            rho |  .75737175   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt litxRR democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend 
> russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2289                         Obs per group: min =         5
       between = 0.1410                                        avg =      34.1
       overall = 0.0014                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9997                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .1143224   .1833976     0.62   0.545    -.2852667    .5139114
    firstcruise_lib |  -.0304216   .0095961    -3.17   0.008    -.0513298   -.0095134
             popul1 |  -7.49e-08   2.92e-07    -0.26   0.802    -7.11e-07    5.61e-07
            gdppcip |   2.43e-07   1.37e-06     0.18   0.862    -2.74e-06    3.23e-06
       literacy_qrt |   .0009046   .0064817     0.14   0.891    -.0132179    .0150271
             litxRR |   .0463344   .0482215     0.96   0.356    -.0587312    .1514001
          democracy |   .0137647   .0018741     7.34   0.000     .0096815     .017848
austriahungarytrend |   .0000252    .000024     1.05   0.314     -.000027    .0000775
         chinatrend |   .0018819   .0038435     0.49   0.633    -.0064923    .0102562
        francetrend |   .0000483   .0000483     1.00   0.338    -.0000571    .0001536
         italytrend |   .0001422   .0001624     0.88   0.398    -.0002115     .000496
         japantrend |   .0009285    .000234     3.97   0.002     .0004187    .0014384
   netherlandstrend |   .0002431   .0000117    20.77   0.000     .0002176    .0002686
       germanytrend |   .0001131   .0000869     1.30   0.218    -.0000763    .0003025
        russiatrend |   5.37e-06   .0001698     0.03   0.975    -.0003645    .0003752
         spaintrend |  -.0002399   1.85e-06  -129.80   0.000     -.000244   -.0002359
        swedentrend |  -.0002056   .0001784    -1.15   0.271    -.0005943     .000183
           usatrend |   .0007498   .0006181     1.21   0.248    -.0005969    .0020964
            uktrend |   .0000301   .0000223     1.35   0.202    -.0000185    .0000788
          ottotrend |    .000033   .0000114     2.90   0.013     8.18e-06    .0000578
              _cons |  -.2656209   .2092591    -1.27   0.228    -.7215574    .1903156
--------------------+----------------------------------------------------------------
            sigma_u |  1.1336218
            sigma_e |  .02093529
                rho |  .99965906   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /* Ngram measure of Nationalism  */
> 
> corr military1 ngramnation2 if waryear==1 & country=="France";
(obs=81)

             | milita~1 ngramn~2
-------------+------------------
   military1 |   1.0000
ngramnation2 |   0.0948   1.0000


. corr military1 ngramnation2 if waryear==1 & country=="Prussia/Germany";
(obs=31)

             | milita~1 ngramn~2
-------------+------------------
   military1 |   1.0000
ngramnation2 |   0.5867   1.0000


. corr military1 ngramnation2 if waryear==1 & country=="United Kingdom";
(obs=109)

             | milita~1 ngramn~2
-------------+------------------
   military1 |   1.0000
ngramnation2 |   0.0804   1.0000


. corr mobil ngramnation2 if waryear==1 & country=="France";
(obs=81)

             |    mobil ngramn~2
-------------+------------------
       mobil |   1.0000
ngramnation2 |   0.0987   1.0000


. corr mobil ngramnation2 if waryear==1 & country=="Prussia/Germany";
(obs=31)

             |    mobil ngramn~2
-------------+------------------
       mobil |   1.0000
ngramnation2 |   0.3443   1.0000


. corr mobil ngramnation2 if waryear==1 & country=="United Kingdom";
(obs=109)

             |    mobil ngramn~2
-------------+------------------
       mobil |   1.0000
ngramnation2 |   0.1828   1.0000


. xtreg military1 RRkmip1 firstcruise_lib popul2 gdppcip2 ngramnation2 democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       221
Group variable: countryno                       Number of groups   =         3

R-sq:  within  = 0.5731                         Obs per group: min =        31
       between = 0.9061                                        avg =      73.7
       overall = 0.5884                                        max =       109

                                                F(2,2)             =         .
corr(u_i, Xb)  = 0.1759                         Prob > F           =         .

                                 (Std. Err. adjusted for 3 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   56245.94   3375.148    16.66   0.004     41723.85    70768.02
firstcruise_lib |  -1631.983   1482.919    -1.10   0.386     -8012.47    4748.505
         popul2 |   24693.99     7504.7     3.29   0.081    -7596.127    56984.11
       gdppcip2 |   80.15802    175.327     0.46   0.692    -674.2133    834.5293
   ngramnation2 |   35128.24   2527.153    13.90   0.005     24254.78     46001.7
      democracy |  -154.9893   171.1783    -0.91   0.461      -891.51    581.5315
           year |  -5.961047   2.289534    -2.60   0.121    -15.81212    3.890022
          _cons |   9885.994   3803.817     2.60   0.122    -6480.511     26252.5
----------------+----------------------------------------------------------------
        sigma_u |  499.88639
        sigma_e |  960.79449
            rho |  .21302962   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul2 gdppcip2 ngramnation2 democracy francetrend germanytrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       221
Group variable: countryno                       Number of groups   =         3

R-sq:  within  = 0.5742                         Obs per group: min =        31
       between = 0.9142                                        avg =      73.7
       overall = 0.1616                                        max =       109

                                                F(2,2)             =         .
corr(u_i, Xb)  = -0.9917                        Prob > F           =         .

                                 (Std. Err. adjusted for 3 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   48094.54   7768.613     6.19   0.025      14668.9    81520.19
firstcruise_lib |  -1826.035   1440.352    -1.27   0.332    -8023.371    4371.301
         popul2 |  -1863.397    18009.5    -0.10   0.927    -79352.01    75625.21
       gdppcip2 |   92.08814   142.7072     0.65   0.585    -521.9315    706.1078
   ngramnation2 |   21304.32   11877.94     1.79   0.215    -29802.33    72410.96
      democracy |  -53.95305   321.8514    -0.17   0.882    -1438.768    1330.862
    francetrend |  -2.710934   .3406828    -7.96   0.015    -4.176773   -1.245094
   germanytrend |    11.5448   7.941994     1.45   0.283    -22.62685    45.71644
          _cons |   -1257.49   1796.589    -0.70   0.556     -8987.59    6472.611
----------------+----------------------------------------------------------------
        sigma_u |  13461.866
        sigma_e |  961.89715
            rho |  .99492034   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 ngramnation2 democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       221
Group variable: countryno                       Number of groups   =         3

R-sq:  within  = 0.3153                         Obs per group: min =        31
       between = 0.1692                                        avg =      73.7
       overall = 0.2957                                        max =       109

                                                F(2,2)             =         .
corr(u_i, Xb)  = 0.0006                         Prob > F           =         .

                                 (Std. Err. adjusted for 3 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   1.226602    .148591     8.25   0.014     .5872669    1.865937
firstcruise_lib |  -.0258765    .032796    -0.79   0.513    -.1669865    .1152335
         popul2 |  -.5392357   .0832014    -6.48   0.023    -.8972225   -.1812489
       gdppcip2 |   .0012559   .0037271     0.34   0.768    -.0147807    .0172925
   ngramnation2 |   .8835538   .0799365    11.05   0.008     .5396147    1.227493
      democracy |    .006302   .0008764     7.19   0.019     .0025312    .0100729
           year |  -.0000371   .0000476    -0.78   0.517    -.0002418    .0001676
          _cons |   .0785377   .0772422     1.02   0.416    -.2538088    .4108841
----------------+----------------------------------------------------------------
        sigma_u |  .01136356
        sigma_e |  .02302677
            rho |   .1958414   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 ngramnation2 democracy francetrend germanytrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       221
Group variable: countryno                       Number of groups   =         3

R-sq:  within  = 0.3190                         Obs per group: min =        31
       between = 0.2890                                        avg =      73.7
       overall = 0.0511                                        max =       109

                                                F(2,2)             =         .
corr(u_i, Xb)  = -0.9449                        Prob > F           =         .

                                 (Std. Err. adjusted for 3 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   1.362001   .2770029     4.92   0.039     .1701532    2.553848
firstcruise_lib |  -.0215829   .0335302    -0.64   0.586    -.1658518    .1226861
         popul2 |  -.7423418   .2445482    -3.04   0.094    -1.794548     .309864
       gdppcip2 |   .0011348   .0033638     0.34   0.768    -.0133387    .0156083
   ngramnation2 |   .8713971   .2202964     3.96   0.058    -.0764618    1.819256
      democracy |   .0049648   .0034773     1.43   0.290    -.0099968    .0199263
    francetrend |  -.0000516   6.04e-06    -8.54   0.013    -.0000776   -.0000256
   germanytrend |   .0000111   .0001101     0.10   0.929    -.0004627    .0004848
          _cons |   .0470086   .0265668     1.77   0.219    -.0672992    .1613164
----------------+----------------------------------------------------------------
        sigma_u |  .05764239
        sigma_e |  .02301793
            rho |  .86247139   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. /* Democracy and RR interaction */
> 
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt demxRR democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4448                         Obs per group: min =         5
       between = 0.7475                                        avg =      34.1
       overall = 0.3885                                        max =       109

                                                F(8,12)            =  41501.31
corr(u_i, Xb)  = -0.8866                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   43151.47   6070.835     7.11   0.000     29924.26    56378.68
firstcruise_lib |  -3573.369   592.8336    -6.03   0.000    -4865.043   -2281.696
         popul1 |   .0103971   .0012832     8.10   0.000     .0076012     .013193
        gdppcip |    .282449    .128375     2.20   0.048     .0027439    .5621541
   literacy_qrt |  -129.3984     108.51    -1.19   0.256    -365.8213    107.0245
         demxRR |  -17454.75   11352.98    -1.54   0.150    -42190.77    7281.269
      democracy |  -113.8718   705.4928    -0.16   0.874    -1651.009    1423.265
           year |  -1.163276   1.396939    -0.83   0.421    -4.206944    1.880392
          _cons |   1462.965   2164.963     0.68   0.512    -3254.085    6180.015
----------------+----------------------------------------------------------------
        sigma_u |  2366.7799
        sigma_e |  1207.0201
            rho |  .79359804   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt demxRR democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytr
> end russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4646                         Obs per group: min =         5
       between = 0.1913                                        avg =      34.1
       overall = 0.0049                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9994                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   37216.11   9480.742     3.93   0.002     16559.35    57872.87
    firstcruise_lib |  -3269.159   959.6282    -3.41   0.005    -5360.009   -1178.308
             popul1 |   .0199249   .0208603     0.96   0.358    -.0255258    .0653756
            gdppcip |   .1967468   .1580203     1.25   0.237    -.1475498    .5410433
       literacy_qrt |  -115.9216   177.6169    -0.65   0.526    -502.9156    271.0725
             demxRR |  -7519.249   12379.12    -0.61   0.555    -34491.04    19452.54
          democracy |   40.42289   455.4367     0.09   0.931    -951.8885    1032.734
austriahungarytrend |   -1.30974   1.192974    -1.10   0.294    -3.909007    1.289527
         chinatrend |  -164.8503   311.5072    -0.53   0.606    -843.5661    513.8655
        francetrend |  -1.837905   1.525274    -1.20   0.251    -5.161191    1.485381
         italytrend |   2.703748   4.257356     0.64   0.537    -6.572235    11.97973
         japantrend |   41.30171   10.37742     3.98   0.002     18.69125    63.91217
   netherlandstrend |  -1.085834   1.263854    -0.86   0.407    -3.839536    1.667868
       germanytrend |   4.146572   4.717168     0.88   0.397    -6.131254     14.4244
        russiatrend |  -9.947391   12.38533    -0.80   0.438     -36.9327    17.03792
         spaintrend |  -2.094559   .1262252   -16.59   0.000     -2.36958   -1.819538
        swedentrend |    3.30312   4.895142     0.67   0.513    -7.362479    13.96872
           usatrend |    7.09305   35.86234     0.20   0.847    -71.04428    85.23038
            uktrend |  -2.787636   1.743962    -1.60   0.136    -6.587403    1.012131
          ottotrend |   1.296631    .895327     1.45   0.173    -.6541192    3.247381
              _cons |   3259.829   16017.46     0.20   0.842    -31639.21    38158.87
--------------------+----------------------------------------------------------------
            sigma_u |   91900.44
            sigma_e |  1202.5956
                rho |  .99982879   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt demxRR democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1923                         Obs per group: min =         5
       between = 0.0254                                        avg =      34.1
       overall = 0.0405                                        max =       109

                                                F(8,12)            =   1989.13
corr(u_i, Xb)  = -0.7537                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2233377   .1371969     1.63   0.130    -.0755887    .5222641
firstcruise_lib |   -.030787   .0091197    -3.38   0.006    -.0506571   -.0109169
         popul1 |   2.94e-08   4.63e-08     0.63   0.538    -7.16e-08    1.30e-07
        gdppcip |   1.18e-06   1.52e-06     0.78   0.452    -2.12e-06    4.48e-06
   literacy_qrt |   .0005198   .0033831     0.15   0.880    -.0068513    .0078909
         demxRR |   -.040102   .1498519    -0.27   0.794    -.3666012    .2863973
      democracy |   .0142358    .005898     2.41   0.033     .0013851    .0270865
           year |   .0000175   .0000189     0.92   0.374    -.0000237    .0000587
          _cons |  -.0222295   .0290069    -0.77   0.458      -.08543     .040971
----------------+----------------------------------------------------------------
        sigma_u |  .03229179
        sigma_e |  .02112038
            rho |  .70038871   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt demxRR democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend 
> russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2318                         Obs per group: min =         5
       between = 0.1411                                        avg =      34.1
       overall = 0.0040                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .5121572   .2523047     2.03   0.065    -.0375675    1.061882
    firstcruise_lib |  -.0298246   .0084499    -3.53   0.004    -.0482354   -.0114138
             popul1 |  -2.21e-07   3.36e-07    -0.66   0.523    -9.53e-07    5.11e-07
            gdppcip |   2.50e-07   1.19e-06     0.21   0.837    -2.34e-06    2.84e-06
       literacy_qrt |   .0009084   .0052518     0.17   0.866    -.0105342    .0123511
             demxRR |   -.307387   .2720098    -1.13   0.281    -.9000455    .2852714
          democracy |   .0198412   .0037995     5.22   0.000     .0115627    .0281196
austriahungarytrend |   .0000368   .0000177     2.08   0.059    -1.70e-06    .0000753
         chinatrend |   .0037355   .0044951     0.83   0.422    -.0060586    .0135296
        francetrend |   .0000454   .0000377     1.20   0.252    -.0000368    .0001276
         italytrend |    .000151   .0001377     1.10   0.294    -.0001489     .000451
         japantrend |   .0009283   .0002054     4.52   0.001     .0004808    .0013758
   netherlandstrend |   .0002436     .00001    24.26   0.000     .0002217    .0002655
       germanytrend |   .0001009   .0000812     1.24   0.238     -.000076    .0002778
        russiatrend |   8.44e-06   .0001723     0.05   0.962     -.000367    .0003839
         spaintrend |   -.000239   2.11e-06  -113.47   0.000    -.0002436   -.0002344
        swedentrend |  -.0002057   .0001444    -1.42   0.180    -.0005204    .0001089
           usatrend |   .0009527   .0006475     1.47   0.167     -.000458    .0023635
            uktrend |   .0000423   .0000203     2.09   0.059    -1.88e-06    .0000865
          ottotrend |   .0000271   .0000134     2.03   0.065    -1.96e-06    .0000562
              _cons |  -.3466061   .2348365    -1.48   0.166    -.8582709    .1650588
--------------------+----------------------------------------------------------------
            sigma_u |  2.0297358
            sigma_e |  .02089602
                rho |  .99989403   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 in log levels **/
> xtreg lnmilitary1 RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.5375                         Obs per group: min =         5
       between = 0.5512                                        avg =      34.1
       overall = 0.4822                                        max =       109

                                                F(5,12)            =    102.01
corr(u_i, Xb)  = -0.7551                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
    lnmilitary1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |    17.3661   5.648643     3.07   0.010     5.058764    29.67344
firstcruise_lib |   .2615131   .2998765     0.87   0.400    -.3918618    .9148879
         gt1789 |    .932026   .1864428     5.00   0.000     .5258021     1.33825
         gt1859 |   .6678184   .3388616     1.97   0.072    -.0704975    1.406134
         gt1970 |  -.1982453   .2699751    -0.73   0.477    -.7864705    .3899799
          _cons |   11.47073   .1534097    74.77   0.000     11.13648    11.80498
----------------+----------------------------------------------------------------
        sigma_u |  1.3715287
        sigma_e |  .75663156
            rho |  .76667123   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg lnmilitary1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.6407                         Obs per group: min =         5
       between = 0.8707                                        avg =      34.1
       overall = 0.6567                                        max =       109

                                                F(7,12)            =    614.16
corr(u_i, Xb)  = -0.7594                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
    lnmilitary1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   9.470521   5.303839     1.79   0.099    -2.085551    21.02659
firstcruise_lib |  -1.674958   .5411073    -3.10   0.009    -2.853929   -.4959866
         popul1 |   6.29e-06   2.71e-06     2.32   0.039     3.90e-07    .0000122
        gdppcip |   .0000899   .0000566     1.59   0.138    -.0000334    .0002131
   literacy_qrt |  -.1967019   .1069765    -1.84   0.091    -.4297837    .0363799
      democracy |  -.2166594    .314689    -0.69   0.504    -.9023078    .4689891
           year |   .0100117    .000741    13.51   0.000     .0083973    .0116262
          _cons |    -5.6139   1.313568    -4.27   0.001    -8.475919    -2.75188
----------------+----------------------------------------------------------------
        sigma_u |  1.2481848
        sigma_e |  .66847025
            rho |  .77711067   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg lnmilitary1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend r
> ussiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.7070                         Obs per group: min =         5
       between = 0.0071                                        avg =      34.1
       overall = 0.0179                                        max =       109

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9989                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
        lnmilitary1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   11.47911   3.302608     3.48   0.005     4.283349    18.67488
    firstcruise_lib |  -1.092562   .3510746    -3.11   0.009    -1.857488   -.3276359
             popul1 |   7.94e-06   6.80e-06     1.17   0.265    -6.87e-06    .0000228
            gdppcip |  -.0000441   .0000341    -1.29   0.221    -.0001184    .0000303
       literacy_qrt |   -.162801   .1431451    -1.14   0.278    -.4746874    .1490854
          democracy |   .0968706   .1414696     0.68   0.507    -.2113651    .4051064
austriahungarytrend |   .0101421   .0009519    10.65   0.000      .008068    .0122162
         chinatrend |   -.069638   .0951093    -0.73   0.478    -.2768633    .1375874
        francetrend |     .00803   .0008741     9.19   0.000     .0061254    .0099345
         italytrend |   .0241615   .0041063     5.88   0.000     .0152146    .0331084
         japantrend |   .0423255   .0060253     7.02   0.000     .0291975    .0554535
   netherlandstrend |   .0086711   .0002785    31.14   0.000     .0080644    .0092778
       germanytrend |    .017859   .0029772     6.00   0.000     .0113723    .0243457
        russiatrend |   .0042229   .0054606     0.77   0.454    -.0076748    .0161206
         spaintrend |  -.0160507   .0000422  -380.28   0.000    -.0161427   -.0159587
        swedentrend |   .0142209   .0039391     3.61   0.004     .0056384    .0228035
           usatrend |   .0405638    .011312     3.59   0.004      .015917    .0652106
            uktrend |   .0122195   .0004652    26.27   0.000     .0112059     .013233
          ottotrend |   .0043506   .0002765    15.73   0.000     .0037481    .0049531
              _cons |    -9.6494   5.372469    -1.80   0.098      -21.355    2.056204
--------------------+----------------------------------------------------------------
            sigma_u |  53.087843
            sigma_e |  .61237512
                rho |  .99986696   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Table 2 and 3 with year fixed effects **/
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy i.year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.7800                         Obs per group: min =         5
       between = 0.5733                                        avg =      34.1
       overall = 0.4033                                        max =       109

                                                F(12,12)           =         .
corr(u_i, Xb)  = -0.9068                        Prob > F           =         .

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |    28663.4   8154.323     3.52   0.004     10896.66    46430.15
firstcruise_lib |   769.0476    837.228     0.92   0.376    -1055.116    2593.211
         popul1 |   .0196051    .005171     3.79   0.003     .0083386    .0308717
        gdppcip |   .8171296   .3471308     2.35   0.036     .0607966    1.573463
   literacy_qrt |   44.20274   331.2059     0.13   0.896    -677.4329    765.8384
      democracy |  -340.3219   781.0816    -0.44   0.671    -2042.153    1361.509
                |
           year |
          1618  |   211.0838   123.2816     1.71   0.113    -57.52374    479.6913
          1625  |   121.8438   122.1558     1.00   0.338    -144.3108    387.9984
          1626  |   66.20095   124.1363     0.53   0.604    -204.2688    336.6707
          1627  |    95.1909   123.9195     0.77   0.457    -174.8066    365.1884
          1628  |   104.1808   123.7049     0.84   0.416     -165.349    373.7107
          1629  |   148.7216   104.4398     1.42   0.180    -78.83324    376.2764
          1630  |  -218.2946   196.8528    -1.11   0.289    -647.2001    210.6108
          1632  |   16.40856    403.125     0.04   0.968    -861.9254    894.7425
          1635  |  -107.7114    206.103    -0.52   0.611    -556.7712    341.3484
          1636  |   -545.673   211.3368    -2.58   0.024    -1006.136   -85.20973
          1637  |   -342.591   248.0377    -1.38   0.192    -883.0187    197.8366
          1640  |   89.46106   69.20144     1.29   0.220    -61.31593    240.2381
          1645  |    55.4559   59.34076     0.93   0.368     -73.8365    184.7483
          1652  |   239.5407   412.9555     0.58   0.573    -660.2121    1139.293
          1655  |  -66.61565   65.23123    -1.02   0.327    -208.7423    75.51098
          1656  |  -2.496664   119.2197    -0.02   0.984    -262.2541    257.2607
          1657  |  -56.15648   46.24848    -1.21   0.248    -156.9233    44.61029
          1660  |  -330.3916   204.1761    -1.62   0.132    -775.2532    114.4699
          1661  |    -4.1103   119.0287    -0.03   0.973    -263.4515    255.2309
          1664  |  -44.13847   118.9496    -0.37   0.717    -303.3074    215.0305
          1667  |  -101.1668   52.69454    -1.92   0.079    -215.9783    13.64473
          1668  |  -515.6445   211.6078    -2.44   0.031    -976.6983   -54.59079
          1672  |   -104.172   60.87502    -1.71   0.113    -236.8073    28.46332
          1673  |    -29.123    118.873    -0.24   0.811    -288.1249    229.8789
          1675  |  -96.76067   55.31131    -1.75   0.106    -217.2737    23.75232
          1677  |  -21.77291   118.9163    -0.18   0.858    -280.8692    237.3234
          1678  |  -146.3892   122.1868    -1.20   0.254    -412.6114    119.8331
          1683  |  -59.55027   119.0703    -0.50   0.626    -318.9823    199.8817
          1684  |  -262.6419   158.0584    -1.66   0.122    -607.0216     81.7378
          1685  |  -60.53573   119.1454    -0.51   0.621    -320.1313    199.0598
          1687  |   -78.8562    94.3237    -0.84   0.419    -284.3699    126.6575
          1688  |   81.07363   177.6467     0.46   0.656    -305.9854    468.1326
          1689  |   103.4847   177.3191     0.58   0.570    -282.8604    489.8299
          1690  |  -84.90416   88.15629    -0.96   0.354    -276.9802    107.1719
          1691  |   7.908568   126.4741     0.06   0.951    -267.6547    283.4719
          1692  |    -70.154   156.5055    -0.45   0.662    -411.1502    270.8422
          1693  |  -91.79519   80.51948    -1.14   0.277    -267.2321    83.64169
          1694  |   38.66176   115.8646     0.33   0.744    -213.7855     291.109
          1695  |   32.67069   140.1566     0.23   0.820    -272.7042    338.0456
          1696  |    5.19392     116.26     0.04   0.965    -248.1149    258.5028
          1697  |   30.04506   139.3078     0.22   0.833    -273.4805    333.5706
          1698  |  -53.90172   98.60808    -0.55   0.595    -268.7503    160.9468
          1699  |  -61.57888   120.0003    -0.51   0.617    -323.0371    199.8794
          1700  |  -90.04025   186.6409    -0.48   0.638    -496.6959    316.6154
          1701  |  -7.550043   126.4794    -0.06   0.953    -283.1249    268.0249
          1702  |   11.37558   128.1031     0.09   0.931    -267.7372    290.4883
          1703  |   17.72026   128.2723     0.14   0.892    -261.7611    297.2016
          1704  |   21.03721   128.3074     0.16   0.872    -258.5207    300.5951
          1705  |  -45.08321   99.24894    -0.45   0.658    -261.3281    171.1617
          1706  |   11.29296    131.522     0.09   0.933    -275.2688    297.8548
          1707  |  -58.99852   129.1854    -0.46   0.656    -340.4693    222.4723
          1708  |  -121.4395    170.719    -0.71   0.490    -493.4041    250.5252
          1709  |   4.980616   132.0567     0.04   0.971    -282.7461    292.7074
          1710  |  -133.7677   85.58763    -1.56   0.144    -320.2471    52.71172
          1711  |   19.13607   139.0317     0.14   0.893    -283.7879    322.0601
          1712  |   15.67793   142.3213     0.11   0.914    -294.4136    325.7694
          1713  |  -47.56445   122.4086    -0.39   0.704    -314.2699     219.141
          1714  |  -32.63771     166.41    -0.20   0.848    -395.2139    329.9385
          1715  |  -23.40976    166.127    -0.14   0.890    -385.3695      338.55
          1716  |   -49.2718   121.7958    -0.40   0.693    -314.6421    216.0985
          1717  |   -48.7527   121.9348    -0.40   0.696    -314.4259    216.9205
          1718  |  -43.53779    121.298    -0.36   0.726    -307.8234    220.7478
          1719  |  -44.40035   121.1278    -0.37   0.720    -308.3152    219.5145
          1720  |  -55.44735    122.374    -0.45   0.659    -322.0773    211.1826
          1721  |   -507.006   713.4009    -0.71   0.491    -2061.373    1047.361
          1728  |   -53.8385   163.0613    -0.33   0.747    -409.1186    301.4416
          1729  |  -54.91028   163.1414    -0.34   0.742    -410.3648    300.5443
          1733  |  -321.0539   147.5881    -2.18   0.050    -642.6208    .5129246
          1734  |  -382.4492   277.2129    -1.38   0.193    -986.4443    221.5458
          1735  |  -308.6251   180.6024    -1.71   0.113    -702.1239    84.87362
          1736  |  -328.3525    165.722    -1.98   0.071    -689.4296    32.72465
          1737  |  -104.9004   125.4716    -0.84   0.419    -378.2795    168.4786
          1738  |  -110.8533   125.6851    -0.88   0.395    -384.6976    162.9909
          1739  |  -104.7833   120.8935    -0.87   0.403    -368.1876     158.621
          1740  |  -265.0946   196.5751    -1.35   0.202     -693.395    163.2058
          1741  |   -95.8919   129.8997    -0.74   0.475     -378.919    187.1352
          1742  |  -265.1168   94.01629    -2.82   0.015    -469.9607   -60.27291
          1743  |   -230.975   104.1927    -2.22   0.047    -457.9914   -3.958614
          1744  |  -248.6536   91.48705    -2.72   0.019    -447.9867   -49.32039
          1745  |  -206.3153   95.94726    -2.15   0.053    -415.3664     2.73579
          1746  |  -196.3306   96.29843    -2.04   0.064    -406.1469    13.48564
          1747  |  -195.1511   90.93092    -2.15   0.053    -393.2726    2.970357
          1748  |  -222.7335   98.56943    -2.26   0.043    -437.4978   -7.969143
          1755  |  -238.0134   165.7181    -1.44   0.176     -599.082    123.0553
          1756  |  -340.5084   297.0066    -1.15   0.274    -987.6303    306.6134
          1757  |  -274.3429   292.4849    -0.94   0.367    -911.6128    362.9271
          1758  |   -263.459   292.5296    -0.90   0.386    -900.8261    373.9082
          1759  |  -113.2366   202.9363    -0.56   0.587    -555.3968    328.9237
          1760  |  -107.0257   205.9839    -0.52   0.613    -555.8261    341.7747
          1761  |  -270.2891   301.5433    -0.90   0.388    -927.2955    386.7173
          1762  |  -116.1203   216.4184    -0.54   0.601    -587.6556     355.415
          1763  |  -289.3833   334.1878    -0.87   0.404    -1017.516    438.7494
          1778  |  -379.8622   302.2609    -1.26   0.233    -1038.432    278.7078
          1779  |   -333.415   318.0003    -1.05   0.315    -1026.278     359.448
          1780  |  -405.1112   340.2762    -1.19   0.257    -1146.509    336.2871
          1781  |   -406.296   341.5156    -1.19   0.257    -1150.394    337.8026
          1782  |  -408.0232   343.6981    -1.19   0.258    -1156.877    340.8305
          1783  |  -426.9373   326.8566    -1.31   0.216    -1139.097    285.2221
          1784  |  -701.9336   320.6097    -2.19   0.049    -1400.482   -3.385055
          1787  |  -327.2897   284.7063    -1.15   0.273    -947.6114    293.0321
          1788  |   -242.509   284.3809    -0.85   0.410    -862.1218    377.1039
          1789  |  -248.9812    284.064    -0.88   0.398    -867.9036    369.9411
          1790  |  -256.4325   283.7555    -0.90   0.384    -874.6827    361.8177
          1791  |  -363.1888   283.4555    -1.28   0.224    -980.7854    254.4077
          1792  |  -328.2364   165.4159    -1.98   0.071    -688.6467    32.17387
          1793  |  -270.9061   199.3745    -1.36   0.199    -705.3058    163.4935
          1794  |  -138.1806   221.7934    -0.62   0.545     -621.427    345.0658
          1795  |  -358.2669   347.0231    -1.03   0.322    -1114.365    397.8314
          1796  |  -474.1788   396.5213    -1.20   0.255    -1338.124    389.7669
          1797  |  -407.7412   229.0649    -1.78   0.100    -906.8309    91.34841
          1798  |  -163.2632    170.761    -0.96   0.358    -535.3194     208.793
          1799  |  -154.8201   171.1121    -0.90   0.383    -527.6412    218.0011
          1800  |  -467.0809    543.542    -0.86   0.407    -1651.357    717.1954
          1801  |  -491.5502   524.1912    -0.94   0.367    -1633.665    650.5643
          1802  |  -275.9377   395.4468    -0.70   0.499    -1137.542     585.667
          1803  |   -363.061   395.5892    -0.92   0.377    -1224.976    498.8539
          1804  |   -403.399   390.0152    -1.03   0.321    -1253.169    446.3712
          1805  |   -384.027   411.8857    -0.93   0.370    -1281.449    513.3948
          1806  |  -438.6296   395.2583    -1.11   0.289    -1299.823    422.5642
          1807  |  -419.2507   392.9094    -1.07   0.307    -1275.327    436.8253
          1808  |  -425.3719   402.9754    -1.06   0.312     -1303.38    452.6362
          1809  |  -301.5074   367.2633    -0.82   0.428    -1101.705    498.6906
          1810  |  -412.0629   456.4446    -0.90   0.384     -1406.57    582.4445
          1811  |  -476.2043   407.9005    -1.17   0.266    -1364.943    412.5345
          1812  |  -362.2519   390.9694    -0.93   0.372    -1214.101    489.5973
          1813  |  -285.4945   364.9032    -0.78   0.449     -1080.55    509.5613
          1814  |  -213.8373   396.0867    -0.54   0.599    -1076.836    649.1615
          1815  |  -430.3775   450.7298    -0.95   0.358    -1412.433    551.6785
          1823  |  -925.1348   351.9151    -2.63   0.022    -1691.892   -158.3776
          1827  |  -803.3153   483.2366    -1.66   0.122    -1856.197    249.5669
          1828  |  -922.1355   626.0999    -1.47   0.167     -2286.29     442.019
          1829  |  -761.0317   625.9269    -1.22   0.247    -2124.809    602.7458
          1848  |  -858.0637   393.7185    -2.18   0.050    -1715.903   -.2247648
          1849  |  -853.5532   439.2122    -1.94   0.076    -1810.515     103.408
          1853  |  -1399.873   631.2545    -2.22   0.047    -2775.259   -24.48777
          1854  |  -1323.609   709.2097    -1.87   0.087    -2868.845    221.6258
          1855  |    -1071.6   763.4906    -1.40   0.186    -2735.103    591.9027
          1856  |   -987.122   920.7276    -1.07   0.305    -2993.215    1018.971
          1857  |  -1849.778   621.2647    -2.98   0.012    -3203.397   -496.1583
          1859  |  -1361.013     783.55    -1.74   0.108    -3068.222    346.1957
          1862  |  -1708.582   768.4591    -2.22   0.046     -3382.91   -34.25309
          1863  |  -1816.831   781.4601    -2.32   0.038    -3519.486   -114.1756
          1864  |  -1551.728   847.8446    -1.83   0.092    -3399.022    295.5669
          1865  |  -1845.258   757.2572    -2.44   0.031     -3495.18   -195.3364
          1866  |  -1661.883   585.2759    -2.84   0.015     -2937.09   -386.6767
          1867  |   -1827.29   714.3758    -2.56   0.025    -3383.781   -270.7988
          1870  |  -1328.634   834.3296    -1.59   0.137    -3146.482    489.2146
          1871  |  -1324.596   637.0524    -2.08   0.060    -2712.614    63.42171
          1877  |  -2279.169   557.5549    -4.09   0.002    -3493.977   -1064.361
          1878  |  -1966.522   555.6105    -3.54   0.004    -3177.093   -755.9509
          1884  |  -2170.783   821.6225    -2.64   0.021    -3960.944    -380.621
          1885  |  -2174.254   810.5757    -2.68   0.020    -3940.347   -408.1616
          1898  |   516.8189   916.5539     0.56   0.583     -1480.18    2513.818
          1900  |   -2664.43   1027.275    -2.59   0.023     -4902.67   -426.1909
          1904  |  -4323.211   714.0453    -6.05   0.000    -5878.982    -2767.44
          1905  |  -2700.958   1123.816    -2.40   0.033    -5149.541   -252.3738
          1911  |   -3168.66   920.9408    -3.44   0.005    -5175.218   -1162.103
          1912  |  -3075.651   921.4093    -3.34   0.006     -5083.23   -1068.073
          1914  |  -3528.691   1015.859    -3.47   0.005    -5742.058   -1315.325
          1915  |  -552.4639   820.2508    -0.67   0.513    -2339.637    1234.709
          1916  |  -116.3933   1736.743    -0.07   0.948    -3900.431    3667.644
          1917  |  -775.1023    1524.52    -0.51   0.620    -4096.746    2546.542
          1918  |  -520.0208   1366.227    -0.38   0.710    -3496.774    2456.733
          1919  |  -2858.713   1135.959    -2.52   0.027    -5333.755   -383.6708
          1920  |  -2978.185   809.3448    -3.68   0.003    -4741.596   -1214.774
          1921  |  -3532.361   1007.419    -3.51   0.004    -5727.338   -1337.384
          1929  |   -5738.34   888.9396    -6.46   0.000    -7675.173   -3801.507
          1931  |  -3477.417   1140.454    -3.05   0.010    -5962.252   -992.5814
          1932  |  -3531.759    1174.32    -3.01   0.011    -6090.383   -973.1349
          1933  |  -3693.743   1219.343    -3.03   0.010    -6350.462   -1037.024
          1935  |  -2960.353   1322.525    -2.24   0.045    -5841.888   -78.81813
          1936  |  -3984.215   1316.881    -3.03   0.011    -6853.453   -1114.977
          1937  |  -3941.416   1268.563    -3.11   0.009    -6705.376   -1177.456
          1938  |   -4976.57   1681.111    -2.96   0.012    -8639.396   -1313.744
          1939  |   -4729.58   1539.919    -3.07   0.010    -8084.774   -1374.385
          1940  |  -3445.591    1421.78    -2.42   0.032    -6543.383   -347.7997
          1941  |  -3230.894   1852.081    -1.74   0.107    -7266.231    804.4428
          1942  |  -2188.708   1827.592    -1.20   0.254    -6170.689    1793.274
          1943  |   -1825.94   1318.172    -1.39   0.191    -4697.989    1046.109
          1944  |  -1287.012   1553.427    -0.83   0.424     -4671.64    2097.615
          1945  |   639.4547   2175.332     0.29   0.774    -4100.187    5379.096
          1950  |  -5257.388   1949.431    -2.70   0.019    -9504.834   -1009.943
          1951  |  -5271.476   1749.655    -3.01   0.011    -9083.646   -1459.306
          1952  |  -5246.269    1764.62    -2.97   0.012    -9091.045   -1401.492
          1953  |  -5442.622   1820.797    -2.99   0.011    -9409.798   -1475.447
          1956  |  -5969.937   2111.464    -2.83   0.015    -10570.42   -1369.453
          1962  |   -8643.35    1778.47    -4.86   0.000     -12518.3   -4768.397
          1964  |  -8655.652   3347.073    -2.59   0.024     -15948.3   -1363.006
          1965  |  -9223.566    3568.34    -2.58   0.024    -16998.31   -1448.821
          1966  |  -9390.802    3814.29    -2.46   0.030    -17701.43   -1080.179
          1967  |  -9248.196   3891.273    -2.38   0.035    -17726.55   -769.8405
          1968  |  -9497.787   4080.902    -2.33   0.038    -18389.31   -606.2652
          1969  |  -9832.573   4197.021    -2.34   0.037     -18977.1   -688.0499
          1970  |  -10086.47   4156.805    -2.43   0.032    -19143.37   -1029.572
          1971  |  -10671.16   4258.039    -2.51   0.028    -19948.63   -1393.694
          1972  |  -11535.47   4491.438    -2.57   0.025    -21321.48   -1749.468
          1973  |  -12175.06   4759.245    -2.56   0.025    -22544.56   -1805.555
          1978  |  -13688.42   3038.338    -4.51   0.001    -20308.39   -7068.451
          1979  |  -13934.35   3083.053    -4.52   0.001    -20651.75   -7216.958
          1982  |  -11217.27   4788.141    -2.34   0.037    -21649.73    -784.803
          1990  |  -15436.67   7400.529    -2.09   0.059    -31561.03    687.7009
          1991  |  -15311.73   7354.448    -2.08   0.059     -31335.7    712.2335
                |
          _cons |  -1489.835   597.4769    -2.49   0.028    -2791.625   -188.0443
----------------+----------------------------------------------------------------
        sigma_u |  3584.8433
        sigma_e |  1047.6515
            rho |  .92131342   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy i.year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.6664                         Obs per group: min =         5
       between = 0.2290                                        avg =      34.1
       overall = 0.4934                                        max =       109

                                                F(12,12)           =         .
corr(u_i, Xb)  = -0.3634                        Prob > F           =         .

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |  -.0632678   .2110553    -0.30   0.769    -.5231179    .3965823
firstcruise_lib |   .0467319   .0145603     3.21   0.007     .0150078    .0784561
         popul1 |  -2.43e-08   9.19e-08    -0.26   0.796    -2.25e-07    1.76e-07
        gdppcip |   7.10e-06   3.15e-06     2.25   0.044     2.30e-07     .000014
   literacy_qrt |   .0027376   .0051862     0.53   0.607    -.0085622    .0140374
      democracy |   .0134864   .0122641     1.10   0.293    -.0132349    .0402076
                |
           year |
          1618  |  -.0326933   .0026603   -12.29   0.000    -.0384895    -.026897
          1625  |  -.0098828   .0033305    -2.97   0.012    -.0171392   -.0026263
          1626  |  -.0039839   .0039279    -1.01   0.330    -.0125421    .0045743
          1627  |    .000453   .0039257     0.12   0.910    -.0081005    .0090065
          1628  |   .0019499   .0039236     0.50   0.628    -.0065988    .0104986
          1629  |   .0019868   .0028109     0.71   0.493    -.0041376    .0081111
          1630  |  -.0224524   .0156686    -1.43   0.177    -.0565913    .0116866
          1632  |   .1294242   .0085706    15.10   0.000     .1107503     .148098
          1635  |  -.0051255    .009606    -0.53   0.603    -.0260551    .0158041
          1636  |  -.0177432   .0047939    -3.70   0.003    -.0281883   -.0072981
          1637  |  -.0160437   .0051933    -3.09   0.009     -.027359   -.0047285
          1640  |  -.0181871    .002386    -7.62   0.000    -.0233858   -.0129884
          1645  |  -.0189088   .0023387    -8.09   0.000    -.0240045   -.0138132
          1652  |  -.0009226   .0071278    -0.13   0.899    -.0164527    .0146074
          1655  |  -.0125716   .0019652    -6.40   0.000    -.0168535   -.0082898
          1656  |  -.0086102   .0038973    -2.21   0.047    -.0171016   -.0001188
          1657  |  -.0379614   .0022519   -16.86   0.000    -.0428678    -.033055
          1660  |   -.012533   .0051758    -2.42   0.032    -.0238101   -.0012559
          1661  |  -.0073434   .0039146    -1.88   0.085    -.0158724    .0011857
          1664  |   -.011891   .0039251    -3.03   0.010    -.0204431   -.0033389
          1667  |  -.0259279   .0022107   -11.73   0.000    -.0307446   -.0211113
          1668  |  -.0155161   .0047884    -3.24   0.007    -.0259492   -.0050831
          1672  |  -.0092168   .0022013    -4.19   0.001    -.0140131   -.0044206
          1673  |   -.007386   .0039576    -1.87   0.087    -.0160089    .0012369
          1675  |  -.0100002   .0034839    -2.87   0.014    -.0175909   -.0024095
          1677  |  -.0055243   .0039725    -1.39   0.190    -.0141796     .003131
          1678  |  -.0096638   .0041801    -2.31   0.039    -.0187715   -.0005561
          1683  |  -.0085247   .0039952    -2.13   0.054    -.0172294      .00018
          1684  |  -.0098596   .0015041    -6.56   0.000    -.0131368   -.0065824
          1685  |  -.0081602   .0040029    -2.04   0.064    -.0168817    .0005612
          1687  |  -.0074174   .0036558    -2.03   0.065    -.0153828     .000548
          1688  |   -.010589   .0033392    -3.17   0.008    -.0178644   -.0033136
          1689  |  -.0060865     .00334    -1.82   0.093    -.0133636    .0011907
          1690  |  -.0065439   .0029727    -2.20   0.048    -.0130208    -.000067
          1691  |  -.0055299   .0031695    -1.74   0.107    -.0124357    .0013758
          1692  |  -.0048617   .0028953    -1.68   0.119    -.0111699    .0014465
          1693  |   -.005532    .004518    -1.22   0.244    -.0153758    .0043118
          1694  |  -.0031835   .0032022    -0.99   0.340    -.0101604    .0037935
          1695  |  -.0030699   .0046013    -0.67   0.517    -.0130953    .0069555
          1696  |  -.0037042   .0038717    -0.96   0.358      -.01214    .0047316
          1697  |  -.0029414   .0044808    -0.66   0.524    -.0127043    .0068214
          1698  |    -.00516   .0034767    -1.48   0.164    -.0127351    .0024151
          1699  |  -.0053196   .0040583    -1.31   0.214    -.0141618    .0035226
          1700  |  -.0140322   .0032886    -4.27   0.001    -.0211976   -.0068669
          1701  |  -.0085923   .0049791    -1.73   0.110    -.0194409    .0022563
          1702  |  -.0052181   .0037895    -1.38   0.194    -.0134746    .0030385
          1703  |  -.0039002   .0035867    -1.09   0.298    -.0117149    .0039145
          1704  |  -.0030555   .0035045    -0.87   0.400    -.0106913    .0045802
          1705  |  -.0083617   .0060343    -1.39   0.191    -.0215093     .004786
          1706  |  -.0032651   .0035262    -0.93   0.373     -.010948    .0044177
          1707  |   .0004437   .0054853     0.08   0.937    -.0115079    .0123952
          1708  |   .0030142   .0065894     0.46   0.656     -.011343    .0173713
          1709  |  -.0026025   .0038009    -0.68   0.507     -.010884     .005679
          1710  |  -.0042716    .002105    -2.03   0.065     -.008858    .0003148
          1711  |   .0001705   .0053821     0.03   0.975     -.011556     .011897
          1712  |   .0002373   .0060168     0.04   0.969    -.0128721    .0133467
          1713  |  -.0087983   .0054212    -1.62   0.131    -.0206101    .0030134
          1714  |  -.0150419    .003449    -4.36   0.001    -.0225567   -.0075271
          1715  |  -.0132168   .0034518    -3.83   0.002    -.0207377   -.0056959
          1716  |  -.0010133   .0041271    -0.25   0.810    -.0100055    .0079789
          1717  |   -.000807   .0041313    -0.20   0.848    -.0098083    .0081944
          1718  |    -.00723    .006629    -1.09   0.297    -.0216735    .0072134
          1719  |   -.006939   .0062922    -1.10   0.292    -.0206486    .0067705
          1720  |  -.0009313    .004144    -0.22   0.826    -.0099602    .0080977
          1721  |  -.0135343   .0092748    -1.46   0.170    -.0337424    .0066737
          1728  |  -.0116116   .0034989    -3.32   0.006    -.0192351   -.0039881
          1729  |  -.0115094   .0034972    -3.29   0.006    -.0191291   -.0038896
          1733  |  -.0080759   .0015607    -5.17   0.000    -.0114764   -.0046754
          1734  |  -.0088131   .0044018    -2.00   0.068    -.0184037    .0007775
          1735  |  -.0062888   .0036829    -1.71   0.113    -.0143131    .0017356
          1736  |    -.00778   .0023548    -3.30   0.006    -.0129106   -.0026493
          1737  |  -.0024977   .0042185    -0.59   0.565     -.011689    .0066936
          1738  |  -.0028233    .004223    -0.67   0.516    -.0120245    .0063779
          1739  |  -.0077985   .0052651    -1.48   0.164      -.01927    .0036731
          1740  |  -.0046217   .0054634    -0.85   0.414    -.0165253     .007282
          1741  |  -.0050795   .0036676    -1.38   0.191    -.0130705    .0029115
          1742  |  -.0053946   .0024287    -2.22   0.046    -.0106863    -.000103
          1743  |  -.0063866   .0013597    -4.70   0.001    -.0093491   -.0034242
          1744  |  -.0033265   .0032481    -1.02   0.326    -.0104036    .0037506
          1745  |  -.0047713   .0019415    -2.46   0.030    -.0090014   -.0005411
          1746  |  -.0035427   .0015897    -2.23   0.046    -.0070065    -.000079
          1747  |  -.0041186   .0028257    -1.46   0.171    -.0102753    .0020381
          1748  |   -.005304   .0018529    -2.86   0.014    -.0093411   -.0012669
          1755  |  -.0057081   .0067029    -0.85   0.411    -.0203124    .0088963
          1756  |  -.0055779    .006454    -0.86   0.404    -.0196399    .0084842
          1757  |  -.0068727   .0046648    -1.47   0.166    -.0170365    .0032911
          1758  |  -.0055737   .0052093    -1.07   0.306    -.0169238    .0057765
          1759  |  -.0015672   .0047817    -0.33   0.749    -.0119856    .0088512
          1760  |  -.0004888   .0055709    -0.09   0.932    -.0126267    .0116492
          1761  |   -.004854   .0062472    -0.78   0.452    -.0184656    .0087575
          1762  |  -.0002744   .0074895    -0.04   0.971    -.0165926    .0160438
          1763  |  -.0062712   .0061096    -1.03   0.325    -.0195828    .0070404
          1778  |  -.0095061   .0047017    -2.02   0.066    -.0197502    .0007381
          1779  |  -.0059419   .0058344    -1.02   0.329    -.0186539    .0067701
          1780  |  -.0071591    .008518    -0.84   0.417    -.0257182       .0114
          1781  |  -.0070407    .008639    -0.81   0.431    -.0258634     .011782
          1782  |  -.0069193   .0088224    -0.78   0.448    -.0261416     .012303
          1783  |  -.0089786   .0068571    -1.31   0.215     -.023919    .0059618
          1784  |  -.0158391   .0052782    -3.00   0.011    -.0273393    -.004339
          1787  |  -.0079803   .0044891    -1.78   0.101    -.0177612    .0018007
          1788  |  -.0037538   .0045036    -0.83   0.421    -.0135662    .0060587
          1789  |  -.0039251   .0045182    -0.87   0.402    -.0137693    .0059192
          1790  |   -.004137   .0045329    -0.91   0.379    -.0140134    .0057394
          1791  |  -.0088706   .0045478    -1.95   0.075    -.0187794    .0010382
          1792  |  -.0072056   .0051704    -1.39   0.189    -.0184709    .0040598
          1793  |  -.0072975   .0039234    -1.86   0.088    -.0158458    .0012507
          1794  |  -.0069323   .0065839    -1.05   0.313    -.0212774    .0074127
          1795  |  -.0111963   .0124579    -0.90   0.386    -.0383398    .0159472
          1796  |  -.0070478   .0073962    -0.95   0.359    -.0231628    .0090673
          1797  |  -.0059336   .0060032    -0.99   0.342    -.0190134    .0071463
          1798  |   .0013188   .0039879     0.33   0.747    -.0073701    .0100077
          1799  |   .0023606   .0039989     0.59   0.566    -.0063521    .0110734
          1800  |  -.0048123   .0116596    -0.41   0.687    -.0302164    .0205918
          1801  |  -.0079425   .0089231    -0.89   0.391    -.0273842    .0114992
          1802  |  -.0053373   .0062911    -0.85   0.413    -.0190445    .0083698
          1803  |  -.0104823   .0063027    -1.66   0.122    -.0242147    .0032501
          1804  |  -.0066803   .0059555    -1.12   0.284    -.0196561    .0062956
          1805  |  -.0079839   .0084271    -0.95   0.362    -.0263451    .0103773
          1806  |  -.0081504   .0074397    -1.10   0.295    -.0243601    .0080592
          1807  |  -.0102077   .0106339    -0.96   0.356    -.0333771    .0129617
          1808  |  -.0130437   .0145944    -0.89   0.389    -.0448421    .0187547
          1809  |  -.0035026   .0079036    -0.44   0.666    -.0207232     .013718
          1810  |   -.014755   .0175364    -0.84   0.417    -.0529635    .0234536
          1811  |  -.0093833   .0096476    -0.97   0.350    -.0304036    .0116369
          1812  |  -.0080696   .0121847    -0.66   0.520    -.0346178    .0184785
          1813  |   .0053124   .0100964     0.53   0.608    -.0166857    .0273105
          1814  |   .0000468   .0064385     0.01   0.994    -.0139815    .0140751
          1815  |  -.0023931   .0087417    -0.27   0.789    -.0214396    .0166534
          1823  |  -.0188358   .0058074    -3.24   0.007    -.0314891   -.0061825
          1827  |  -.0159551   .0076792    -2.08   0.060    -.0326865    .0007764
          1828  |  -.0133635   .0088684    -1.51   0.158     -.032686     .005959
          1829  |  -.0102905   .0088832    -1.16   0.269    -.0296453    .0090642
          1848  |    -.01028   .0063078    -1.63   0.129    -.0240235    .0034635
          1849  |  -.0201059   .0097133    -2.07   0.061    -.0412694    .0010577
          1853  |  -.0182562   .0097354    -1.88   0.085    -.0394678    .0029555
          1854  |  -.0165774   .0105467    -1.57   0.142    -.0395566    .0064019
          1855  |  -.0113017   .0106202    -1.06   0.308    -.0344411    .0118377
          1856  |  -.0091832   .0121461    -0.76   0.464    -.0356474    .0172809
          1857  |  -.0194307   .0095815    -2.03   0.065    -.0403069    .0014456
          1859  |  -.0180463   .0103514    -1.74   0.107       -.0406    .0045074
          1862  |  -.0201355   .0108699    -1.85   0.089    -.0438189     .003548
          1863  |  -.0212743   .0110165    -1.93   0.077    -.0452772    .0027286
          1864  |  -.0194108   .0105265    -1.84   0.090    -.0423461    .0035245
          1865  |  -.0212853   .0108384    -1.96   0.073    -.0449002    .0023297
          1866  |   -.023258   .0102961    -2.26   0.043    -.0456912   -.0008247
          1867  |  -.0209186   .0104946    -1.99   0.069    -.0437845    .0019473
          1870  |  -.0153157   .0272879    -0.56   0.585    -.0747709    .0441395
          1871  |  -.0190233   .0143773    -1.32   0.210    -.0503487    .0123021
          1877  |  -.0154426   .0106256    -1.45   0.172    -.0385937    .0077085
          1878  |  -.0114794   .0107567    -1.07   0.307    -.0349162    .0119573
          1884  |  -.0348868   .0177261    -1.97   0.073    -.0735087     .003735
          1885  |   -.034708   .0177281    -1.96   0.074    -.0733342    .0039182
          1898  |  -.0101733   .0148363    -0.69   0.506    -.0424988    .0221522
          1900  |  -.0284808   .0199734    -1.43   0.179     -.071999    .0150374
          1904  |  -.0176077   .0176392    -1.00   0.338    -.0560402    .0208248
          1905  |  -.0111988   .0188548    -0.59   0.564    -.0522798    .0298822
          1911  |  -.0386865    .022159    -1.75   0.106    -.0869668    .0095937
          1912  |  -.0357796   .0222023    -1.61   0.133    -.0841543     .012595
          1914  |  -.0293356   .0202545    -1.45   0.173    -.0734663    .0147951
          1915  |   .0299923   .0212608     1.41   0.184    -.0163309    .0763156
          1916  |   .0272094   .0321874     0.85   0.414    -.0429209    .0973398
          1917  |   .0244324    .029604     0.83   0.425    -.0400693     .088934
          1918  |   .0331943   .0320214     1.04   0.320    -.0365744     .102963
          1919  |  -.0082039   .0219883    -0.37   0.716    -.0561122    .0397044
          1920  |  -.0225773   .0221002    -1.02   0.327    -.0707294    .0255748
          1921  |  -.0441415   .0220538    -2.00   0.068    -.0921927    .0039097
          1929  |  -.0240014   .0209886    -1.14   0.275    -.0697317    .0217289
          1931  |  -.0174064   .0245803    -0.71   0.492    -.0709622    .0361494
          1932  |    -.01713   .0249247    -0.69   0.505    -.0714364    .0371763
          1933  |  -.0182883   .0253537    -0.72   0.485    -.0735294    .0369527
          1935  |  -.0219717   .0248557    -0.88   0.394    -.0761275    .0321841
          1936  |  -.0459105   .0248168    -1.85   0.089    -.0999817    .0081607
          1937  |  -.0194062   .0260544    -0.74   0.471    -.0761738    .0373613
          1938  |  -.0217765   .0255628    -0.85   0.411    -.0774731    .0339201
          1939  |  -.0380692   .0292683    -1.30   0.218    -.1018395     .025701
          1940  |  -.0080883   .0330125    -0.25   0.811    -.0800162    .0638397
          1941  |  -.0128247   .0303441    -0.42   0.680    -.0789387    .0532894
          1942  |   .0018466   .0296077     0.06   0.951    -.0626629    .0663562
          1943  |   .0014194   .0303188     0.05   0.963    -.0646397    .0674784
          1944  |   .0077483   .0324508     0.24   0.815     -.062956    .0784525
          1945  |   .0200188   .0379352     0.53   0.607     -.062635    .1026726
          1950  |  -.0511652    .027679    -1.85   0.089    -.1114725    .0091421
          1951  |  -.0497908   .0288991    -1.72   0.111    -.1127566     .013175
          1952  |  -.0494038   .0291479    -1.69   0.116    -.1129115     .014104
          1953  |  -.0505887    .029124    -1.74   0.108    -.1140443     .012867
          1956  |  -.0631685   .0302746    -2.09   0.059    -.1291312    .0027942
          1962  |   -.049593   .0294505    -1.68   0.118    -.1137601    .0145741
          1964  |  -.1044444   .0390009    -2.68   0.020      -.18942   -.0194687
          1965  |  -.1093578   .0409269    -2.67   0.020    -.1985299   -.0201857
          1966  |  -.1124236   .0430853    -2.61   0.023    -.2062985   -.0185487
          1967  |  -.1126339   .0437665    -2.57   0.024    -.2079928   -.0172749
          1968  |  -.1158071    .045443    -2.55   0.026     -.214819   -.0167953
          1969  |  -.1187241   .0464803    -2.55   0.025    -.2199959   -.0174523
          1970  |  -.1198236   .0461447    -2.60   0.023    -.2203641    -.019283
          1971  |  -.1237153   .0470663    -2.63   0.022     -.226264   -.0211667
          1972  |  -.1303872   .0491605    -2.65   0.021    -.2374986   -.0232757
          1973  |  -.1362369   .0515685    -2.64   0.021     -.248595   -.0238788
          1978  |  -.0929151   .0405061    -2.29   0.041    -.1811704   -.0046598
          1979  |  -.0929127   .0413382    -2.25   0.044    -.1829808   -.0028446
          1982  |  -.1575948   .0513467    -3.07   0.010    -.2694696     -.04572
          1990  |  -.1895562   .0717182    -2.64   0.021    -.3458168   -.0332956
          1991  |  -.1885436   .0716303    -2.63   0.022    -.3446126   -.0324745
                |
          _cons |   .0101799   .0083867     1.21   0.248     -.008093    .0284529
----------------+----------------------------------------------------------------
        sigma_u |  .02209014
        sigma_e |  .01871444
            rho |  .58216613   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. /** Table 2 and 3 with control for telegrams **/
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy telegramip year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4407                         Obs per group: min =         5
       between = 0.7005                                        avg =      34.1
       overall = 0.3345                                        max =       109

                                                F(8,12)            =  11494.72
corr(u_i, Xb)  = -0.9249                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |    33454.5   6909.489     4.84   0.000     18400.02    48508.99
firstcruise_lib |   -3730.54   593.6821    -6.28   0.000    -5024.062   -2437.017
         popul1 |   .0125676   .0021649     5.81   0.000     .0078507    .0172845
        gdppcip |   .3063739   .1259782     2.43   0.032      .031891    .5808567
   literacy_qrt |  -120.8216   96.69187    -1.25   0.235    -331.4951    89.85191
      democracy |  -592.8745   558.4905    -1.06   0.309    -1809.721    623.9717
     telegramip |   .2705533   .3380678     0.80   0.439    -.4660333     1.00714
           year |  -.9307624   1.133475    -0.82   0.428    -3.400392    1.538868
          _cons |   823.6752   1845.835     0.45   0.663    -3198.054    4845.404
----------------+----------------------------------------------------------------
        sigma_u |  3192.9958
        sigma_e |  1211.4938
            rho |  .87415546   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy telegramip austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germa
> nytrend russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4682                         Obs per group: min =         5
       between = 0.2216                                        avg =      34.1
       overall = 0.0119                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   28795.01   1956.249    14.72   0.000     24532.71    33057.31
    firstcruise_lib |  -3417.746   889.6841    -3.84   0.002    -5356.201   -1479.291
             popul1 |   .0234544   .0174621     1.34   0.204    -.0145922     .061501
            gdppcip |   .1978042   .1500871     1.32   0.212    -.1292075     .524816
       literacy_qrt |  -275.9235    323.966    -0.85   0.411    -981.7848    429.9378
          democracy |  -24.92924   320.1119    -0.08   0.939    -722.3931    672.5346
         telegramip |   .8542457   .2925033     2.92   0.013     .2169359    1.491556
austriahungarytrend |   .2093963   1.461745     0.14   0.888    -2.975473    3.394265
         chinatrend |   -200.813   260.5466    -0.77   0.456    -768.4953    366.8694
        francetrend |   .2468432    2.54716     0.10   0.924    -5.302941    5.796628
         italytrend |   9.655852    8.85802     1.09   0.297    -9.644116    28.95582
         japantrend |   41.89621   11.51886     3.64   0.003     16.79877    66.99365
   netherlandstrend |  -1.108585   1.203023    -0.92   0.375    -3.729748    1.512578
       germanytrend |   7.143866   4.331329     1.65   0.125     -2.29329    16.58102
        russiatrend |  -12.60115   11.06102    -1.14   0.277    -36.70105    11.49875
         spaintrend |  -2.116646   .1050951   -20.14   0.000    -2.345629   -1.887663
        swedentrend |   7.710681    8.91645     0.86   0.404     -11.7166    27.13796
           usatrend |   2.421605   30.17183     0.08   0.937    -63.31717    68.16038
            uktrend |   -1.73085   .9374016    -1.85   0.090    -3.773272    .3115729
          ottotrend |   1.437018   .7588763     1.89   0.083    -.2164316    3.090467
              _cons |   2950.141    12500.3     0.24   0.817    -24285.68    30185.97
--------------------+----------------------------------------------------------------
            sigma_u |  110807.55
            sigma_e |  1198.4892
                rho |  .99988303   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy telegramip year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1942                         Obs per group: min =         5
       between = 0.0198                                        avg =      34.1
       overall = 0.0307                                        max =       109

                                                F(8,12)            =    988.63
corr(u_i, Xb)  = -0.8251                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2439994   .0875987     2.79   0.016     .0531381    .4348606
firstcruise_lib |  -.0300224   .0102748    -2.92   0.013    -.0524092   -.0076356
         popul2 |   .0407276   .0383466     1.06   0.309    -.0428225    .1242778
       gdppcip2 |   .0012304   .0015656     0.79   0.447    -.0021808    .0046416
   literacy_qrt |   .0017166   .0033845     0.51   0.621    -.0056576    .0090909
      democracy |   .0120817   .0042329     2.85   0.015     .0028589    .0213044
     telegramip |  -6.88e-06   4.06e-06    -1.70   0.116    -.0000157    1.96e-06
           year |   4.41e-06    .000016     0.28   0.787    -.0000304    .0000392
          _cons |  -.0029887   .0244245    -0.12   0.905     -.056205    .0502276
----------------+----------------------------------------------------------------
        sigma_u |  .03644792
        sigma_e |  .02109538
            rho |  .74907041   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy telegramip austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanyt
> rend russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2283                         Obs per group: min =         5
       between = 0.1440                                        avg =      34.1
       overall = 0.0018                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .2910065   .1209411     2.41   0.033     .0274986    .5545144
    firstcruise_lib |  -.0299647   .0103037    -2.91   0.013    -.0524145   -.0075149
             popul2 |  -.1009653   .2727012    -0.37   0.718    -.6951302    .4931995
           gdppcip2 |   .0002835   .0013599     0.21   0.838    -.0026796    .0032466
       literacy_qrt |   .0014851   .0065286     0.23   0.824    -.0127396    .0157098
          democracy |   .0138265   .0015133     9.14   0.000     .0105293    .0171236
         telegramip |   1.79e-06   5.95e-06     0.30   0.769    -.0000112    .0000148
austriahungarytrend |   .0000232   .0000271     0.86   0.409    -.0000359    .0000823
         chinatrend |   .0021728   .0035979     0.60   0.557    -.0056664    .0100119
        francetrend |    .000043   .0000495     0.87   0.402    -.0000649    .0001509
         italytrend |    .000142   .0001799     0.79   0.445      -.00025     .000534
         japantrend |   .0009484    .000218     4.35   0.001     .0004734    .0014233
   netherlandstrend |   .0002428   .0000117    20.83   0.000     .0002174    .0002682
       germanytrend |   .0001215   .0000747     1.63   0.130    -.0000413    .0002842
        russiatrend |  -4.33e-06   .0001857    -0.02   0.982     -.000409    .0004003
         spaintrend |  -.0002398   1.73e-06  -138.26   0.000    -.0002435    -.000236
        swedentrend |  -.0002217   .0001795    -1.23   0.241    -.0006128    .0001695
           usatrend |    .000781    .000601     1.30   0.218    -.0005285    .0020904
            uktrend |   .0000286   .0000166     1.72   0.110    -7.56e-06    .0000648
          ottotrend |   .0000319   .0000105     3.02   0.011     8.92e-06    .0000549
              _cons |  -.2759132   .1964048    -1.40   0.185    -.7038426    .1520162
--------------------+----------------------------------------------------------------
            sigma_u |  1.2720926
            sigma_e |  .02094389
                rho |  .99972901   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Table 2 and 3 with control for steam and motor ships **/
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy ship_steammotorip year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4401                         Obs per group: min =         5
       between = 0.6900                                        avg =      34.1
       overall = 0.3263                                        max =       109

                                                F(8,12)            =   2064.95
corr(u_i, Xb)  = -0.9296                        Prob > F           =    0.0000

                                  (Std. Err. adjusted for 13 clusters in countryno)
-----------------------------------------------------------------------------------
                  |               Robust
        military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          RRkmip1 |   35035.19   5329.066     6.57   0.000     23424.16    46646.23
  firstcruise_lib |  -3664.475   614.9558    -5.96   0.000    -5004.348   -2324.601
           popul1 |   .0126945   .0025273     5.02   0.000      .007188    .0182011
          gdppcip |   .3059375   .1285835     2.38   0.035      .025778    .5860969
     literacy_qrt |  -85.59851   116.4304    -0.74   0.476    -339.2786    168.0815
        democracy |   -634.609   549.1516    -1.16   0.270    -1831.108    561.8896
ship_steammotorip |  -.0026468   .0056654    -0.47   0.649    -.0149908    .0096971
             year |  -1.240236   1.306375    -0.95   0.361    -4.086582    1.606109
            _cons |   1272.885   2162.698     0.59   0.567    -3439.229    5984.998
------------------+----------------------------------------------------------------
          sigma_u |  3323.1483
          sigma_e |  1212.1393
              rho |  .88257579   (fraction of variance due to u_i)
-----------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy ship_steammotorip austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstren
> d germanytrend russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4649                         Obs per group: min =         5
       between = 0.2219                                        avg =      34.1
       overall = 0.0103                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   31913.03   2528.604    12.62   0.000     26403.67    37422.38
    firstcruise_lib |  -3407.151   978.0039    -3.48   0.005    -5538.038   -1276.264
             popul1 |    .024051   .0153382     1.57   0.143     -.009368      .05747
            gdppcip |   .2001852   .1570661     1.27   0.227    -.1420325    .5424029
       literacy_qrt |  -83.31387   197.0851    -0.42   0.680    -512.7255    346.0977
          democracy |  -24.99683    288.441    -0.09   0.932    -653.4558    603.4622
  ship_steammotorip |   .0117368    .003336     3.52   0.004     .0044684    .0190052
austriahungarytrend |  -2.041333   .6395493    -3.19   0.008    -3.434792   -.6478751
         chinatrend |  -216.4726    240.406    -0.90   0.386    -740.2722     307.327
        francetrend |   -2.57916   1.717981    -1.50   0.159     -6.32232    1.163999
         italytrend |   1.485154    4.98024     0.30   0.771    -9.365857    12.33617
         japantrend |   40.35913   10.54172     3.83   0.002     17.39068    63.32757
   netherlandstrend |  -1.130549   1.261813    -0.90   0.388    -3.879802    1.618705
       germanytrend |   3.622328   5.030572     0.72   0.485    -7.338347      14.583
        russiatrend |  -11.29036   11.49723    -0.98   0.345    -36.34068    13.75995
         spaintrend |  -2.120507   .0913743   -23.21   0.000    -2.319594   -1.921419
        swedentrend |   2.402652   5.441127     0.44   0.667    -9.452545    14.25785
           usatrend |   2.281397   26.94396     0.08   0.934    -56.42446    60.98725
            uktrend |  -4.752876   1.929961    -2.46   0.030    -8.957899   -.5478527
          ottotrend |   1.459097   .6817589     2.14   0.054    -.0263282    2.944522
              _cons |   6883.092   12368.36     0.56   0.588    -20065.26    33831.44
--------------------+----------------------------------------------------------------
            sigma_u |  117947.32
            sigma_e |  1202.1878
                rho |  .99989612   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy ship_steammotorip year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1921                         Obs per group: min =         5
       between = 0.0265                                        avg =      34.1
       overall = 0.0346                                        max =       109

                                                F(8,12)            =   3425.52
corr(u_i, Xb)  = -0.7863                        Prob > F           =    0.0000

                                  (Std. Err. adjusted for 13 clusters in countryno)
-----------------------------------------------------------------------------------
                  |               Robust
            mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          RRkmip1 |   .2047323   .0746473     2.74   0.018     .0420897    .3673749
  firstcruise_lib |  -.0309637   .0090206    -3.43   0.005    -.0506179   -.0113095
           popul2 |   .0345318   .0403015     0.86   0.408    -.0532776    .1223412
         gdppcip2 |   .0012335    .001493     0.83   0.425    -.0020195    .0044865
     literacy_qrt |   .0006112   .0035075     0.17   0.865    -.0070311    .0082534
        democracy |   .0130347   .0047156     2.76   0.017     .0027602    .0233092
ship_steammotorip |  -9.47e-09   7.79e-08    -0.12   0.905    -1.79e-07    1.60e-07
             year |   .0000175   .0000199     0.88   0.396    -.0000258    .0000609
            _cons |  -.0230468   .0307751    -0.75   0.468    -.0900999    .0440062
------------------+----------------------------------------------------------------
          sigma_u |  .03406916
          sigma_e |  .02112189
              rho |  .72235331   (fraction of variance due to u_i)
-----------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy ship_steammotorip austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend g
> ermanytrend russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       443
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2287                         Obs per group: min =         5
       between = 0.1461                                        avg =      34.1
       overall = 0.0017                                        max =       109

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9997                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .2970061   .1109203     2.68   0.020     .0553316    .5386806
    firstcruise_lib |  -.0313113   .0106189    -2.95   0.012    -.0544479   -.0081747
             popul2 |  -.0879332    .265773    -0.33   0.746    -.6670029    .4911365
           gdppcip2 |   .0003138   .0013236     0.24   0.817      -.00257    .0031976
       literacy_qrt |   .0019764   .0053547     0.37   0.718    -.0096906    .0136434
          democracy |   .0146542   .0014855     9.86   0.000     .0114175    .0178909
  ship_steammotorip |   1.37e-07   9.90e-08     1.39   0.190    -7.82e-08    3.53e-07
austriahungarytrend |   .0000156   .0000185     0.85   0.415    -.0000247    .0000559
         chinatrend |   .0020123   .0035381     0.57   0.580    -.0056964    .0097211
        francetrend |   .0000316   .0000342     0.93   0.373    -.0000428     .000106
         italytrend |    .000119   .0001369     0.87   0.402    -.0001792    .0004172
         japantrend |   .0009314     .00022     4.23   0.001      .000452    .0014108
   netherlandstrend |   .0002425   .0000114    21.35   0.000     .0002178    .0002673
       germanytrend |   .0001055   .0000896     1.18   0.262    -.0000898    .0003008
        russiatrend |  -.0000127   .0001757    -0.07   0.944    -.0003955    .0003701
         spaintrend |  -.0002398   1.69e-06  -141.82   0.000    -.0002435   -.0002362
        swedentrend |  -.0002352   .0001473    -1.60   0.136    -.0005561    .0000857
           usatrend |   .0007746   .0005831     1.33   0.209     -.000496    .0020451
            uktrend |   7.35e-06   .0000314     0.23   0.819    -.0000611    .0000757
          ottotrend |   .0000324   .0000103     3.16   0.008       .00001    .0000548
              _cons |  -.2505203   .2102415    -1.19   0.256    -.7085971    .2075565
--------------------+----------------------------------------------------------------
            sigma_u |  1.2042557
            sigma_e |  .02093783
                rho |   .9996978   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 and 3 without observations with large foreign soldiers**/
> 
> xtreg military1 RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1 & samplesel==0, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       423
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.3578                         Obs per group: min =         3
       between = 0.4071                                        avg =      38.5
       overall = 0.2513                                        max =       109

                                                F(5,10)            =    258.94
corr(u_i, Xb)  = -0.9333                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   43707.09   11925.34     3.67   0.004     17135.77    70278.42
firstcruise_lib |  -427.2783   273.9823    -1.56   0.150    -1037.749    183.1924
         gt1789 |   96.67412   84.41112     1.15   0.279    -91.40557    284.7538
         gt1859 |   219.1592   481.2591     0.46   0.659    -853.1529    1291.471
         gt1970 |   353.2559   342.4821     1.03   0.327    -409.8418    1116.354
          _cons |  -450.9373   254.5114    -1.77   0.107    -1018.024    116.1493
----------------+----------------------------------------------------------------
        sigma_u |  3667.6342
        sigma_e |  1321.8763
            rho |  .88503397   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & samplesel==0, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       423
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.4401                         Obs per group: min =         3
       between = 0.6880                                        avg =      38.5
       overall = 0.3205                                        max =       109

                                                F(7,10)            =    358.58
corr(u_i, Xb)  = -0.9303                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   35123.17   5413.005     6.49   0.000     23062.24     47184.1
firstcruise_lib |  -3691.402   644.3455    -5.73   0.000    -5127.093   -2255.711
         popul1 |   .0128213   .0024581     5.22   0.000     .0073444    .0182982
        gdppcip |   .3063255   .1298555     2.36   0.040     .0169893    .5956617
   literacy_qrt |  -89.35393   119.4958    -0.75   0.472    -355.6071    176.8993
      democracy |   -628.003   542.6688    -1.16   0.274    -1837.144    581.1384
           year |   -1.34938   1.433663    -0.94   0.369     -4.54378    1.845019
          _cons |   1432.947   2371.125     0.60   0.559    -3850.249    6716.142
----------------+----------------------------------------------------------------
        sigma_u |  3617.3626
        sigma_e |  1237.2359
            rho |  .89526917   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend rus
> siatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1 & samplesel==0, fe cluster(countryno);
note: netherlandstrend omitted because of collinearity
note: spaintrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       423
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.4641                         Obs per group: min =         3
       between = 0.2286                                        avg =      38.5
       overall = 0.0091                                        max =       109

                                                F(6,10)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 11 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   31969.29   2606.117    12.27   0.000      26162.5    37776.08
    firstcruise_lib |  -3264.736   1011.029    -3.23   0.009     -5517.45   -1012.023
             popul1 |   .0228254   .0163099     1.40   0.192    -.0135154    .0591662
            gdppcip |   .1975505   .1637807     1.21   0.256    -.1673756    .5624766
       literacy_qrt |  -92.40959    201.399    -0.46   0.656    -541.1545    356.3353
          democracy |  -111.1285   370.1239    -0.30   0.770    -935.8161     713.559
austriahungarytrend |  -1.742776   .6806453    -2.56   0.028    -3.259348   -.2262033
         chinatrend |  -203.2011   254.4755    -0.80   0.443    -770.2079    363.8058
        francetrend |  -2.012719   1.673842    -1.20   0.257    -5.742272    1.716834
         italytrend |   2.094624   4.804301     0.44   0.672    -8.610026    12.79927
         japantrend |   41.78834   11.22779     3.72   0.004     16.77126    66.80542
   netherlandstrend |          0  (omitted)
       germanytrend |   4.515234   5.422994     0.83   0.425     -7.56795    16.59842
        russiatrend |  -10.13297    12.3518    -0.82   0.431    -37.65449    17.38856
         spaintrend |          0  (omitted)
        swedentrend |   5.076531   .0985731    51.50   0.000     4.856897    5.296166
           usatrend |   2.916252   28.83943     0.10   0.921      -61.342    67.17451
            uktrend |  -3.197224   1.608892    -1.99   0.075     -6.78206    .3876114
          ottotrend |   1.412048   .7217036     1.96   0.079    -.1960077    3.020104
              _cons |   5251.144   13973.73     0.38   0.715    -25884.28    36386.56
--------------------+----------------------------------------------------------------
            sigma_u |  121810.31
            sigma_e |  1225.6961
                rho |  .99989876   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1 & samplesel==0, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       423
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.1770                         Obs per group: min =         3
       between = 0.0087                                        avg =      38.5
       overall = 0.0520                                        max =       109

                                                F(5,10)            =     72.96
corr(u_i, Xb)  = -0.7902                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2242763   .1070363     2.10   0.063    -.0142154    .4627679
firstcruise_lib |   -.013293   .0026531    -5.01   0.001    -.0192045   -.0073816
         gt1789 |   .0034903   .0021947     1.59   0.143    -.0013998    .0083803
         gt1859 |   .0116665   .0039511     2.95   0.014     .0028629      .02047
         gt1970 |  -.0027335   .0044337    -0.62   0.551    -.0126126    .0071455
          _cons |   .0081988    .002981     2.75   0.020     .0015567    .0148409
----------------+----------------------------------------------------------------
        sigma_u |  .03164044
        sigma_e |  .02073127
            rho |  .69964026   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & samplesel==0, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       423
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.2111                         Obs per group: min =         3
       between = 0.0152                                        avg =      38.5
       overall = 0.0542                                        max =       109

                                                F(7,10)            =   2503.92
corr(u_i, Xb)  = -0.7973                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .1969921   .0765872     2.57   0.028     .0263452    .3676389
firstcruise_lib |  -.0307448   .0092728    -3.32   0.008    -.0514058   -.0100837
         popul1 |   3.31e-08   4.07e-08     0.81   0.435    -5.76e-08    1.24e-07
        gdppcip |   1.20e-06   1.51e-06     0.79   0.448    -2.18e-06    4.57e-06
   literacy_qrt |   .0012683   .0035506     0.36   0.728     -.006643    .0091796
      democracy |   .0128994   .0046819     2.76   0.020     .0024675    .0233312
           year |   .0000136   .0000191     0.71   0.492    -.0000289    .0000561
          _cons |  -.0186564   .0294657    -0.63   0.541      -.08431    .0469972
----------------+----------------------------------------------------------------
        sigma_u |  .03350638
        sigma_e |  .02034655
            rho |  .73059617   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiat
> rend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1 & samplesel==0, fe cluster(countryno);
note: netherlandstrend omitted because of collinearity
note: spaintrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       423
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.2470                         Obs per group: min =         3
       between = 0.1894                                        avg =      38.5
       overall = 0.0056                                        max =       109

                                                F(6,10)            =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                                    (Std. Err. adjusted for 11 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .2971302   .1117861     2.66   0.024     .0480552    .5462052
    firstcruise_lib |  -.0296401    .009616    -3.08   0.012    -.0510658   -.0082144
             popul1 |  -1.03e-07   2.69e-07    -0.38   0.710    -7.03e-07    4.97e-07
            gdppcip |   2.84e-07   1.39e-06     0.20   0.842    -2.81e-06    3.38e-06
       literacy_qrt |   .0019365   .0054991     0.35   0.732    -.0103162    .0141892
          democracy |    .013636   .0019017     7.17   0.000     .0093988    .0178732
austriahungarytrend |   .0000186   .0000189     0.98   0.349    -.0000235    .0000607
         chinatrend |   .0021781   .0036114     0.60   0.560    -.0058687    .0102249
        francetrend |   .0000376   .0000375     1.00   0.339    -.0000459    .0001212
         italytrend |   .0001238   .0001395     0.89   0.396    -.0001871    .0004346
         japantrend |    .000949   .0002199     4.31   0.002     .0004589     .001439
   netherlandstrend |          0  (omitted)
       germanytrend |   .0001158   .0000881     1.31   0.218    -.0000804    .0003121
        russiatrend |   9.75e-07   .0001776     0.01   0.996    -.0003947    .0003966
         spaintrend |          0  (omitted)
        swedentrend |   .0034264   8.39e-07  4083.84   0.000     .0034245    .0034283
           usatrend |   .0007829   .0006004     1.30   0.221    -.0005548    .0021206
            uktrend |   .0000252   .0000232     1.09   0.303    -.0000265    .0000769
          ottotrend |   .0000318   .0000104     3.06   0.012     8.62e-06     .000055
              _cons |  -.3261141   .2220892    -1.47   0.173    -.8209596    .1687314
--------------------+----------------------------------------------------------------
            sigma_u |  1.9827794
            sigma_e |  .02012816
                rho |  .99989696   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 and 3 dropping Russia and/or Prussia/Germany **/
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Russia/Soviet Union", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       404
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.4278                         Obs per group: min =         5
       between = 0.7571                                        avg =      33.7
       overall = 0.3611                                        max =       109

                                                F(7,11)            =    564.22
corr(u_i, Xb)  = -0.9528                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 12 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   34215.96   7249.926     4.72   0.001     18258.98    50172.94
firstcruise_lib |  -4102.009   447.1813    -9.17   0.000    -5086.249    -3117.77
         popul1 |   .0135158     .00286     4.73   0.001      .007221    .0198107
        gdppcip |   .3285602   .1213644     2.71   0.020      .061439    .5956813
   literacy_qrt |   -50.7117   110.5896    -0.46   0.655    -294.1178    192.6944
      democracy |  -704.8865   596.0701    -1.18   0.262    -2016.828    607.0549
           year |   -1.59134   1.389303    -1.15   0.276    -4.649175    1.466495
          _cons |   1712.214    2270.96     0.75   0.467    -3286.134    6710.563
----------------+----------------------------------------------------------------
        sigma_u |  3431.2634
        sigma_e |  1066.5736
            rho |  .91189171   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swede
> ntrend usatrend uktrend ottotrend if waryear==1 & country~="Russia/Soviet Union", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       404
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.4522                         Obs per group: min =         5
       between = 0.1701                                        avg =      33.7
       overall = 0.0003                                        max =       109

                                                F(6,11)            =         .
corr(u_i, Xb)  = -0.9994                        Prob > F           =         .

                                    (Std. Err. adjusted for 12 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   32797.56   2605.908    12.59   0.000        27062    38533.13
    firstcruise_lib |  -3842.469   731.3966    -5.25   0.000    -5452.262   -2232.675
             popul1 |   .0188529   .0135175     1.39   0.191     -.010899    .0486048
            gdppcip |   .2608169   .1503125     1.74   0.111    -.0700187    .5916525
       literacy_qrt |   82.81334    209.535     0.40   0.700      -378.37    543.9967
          democracy |  -274.5837   390.5554    -0.70   0.497     -1134.19    585.0231
austriahungarytrend |  -3.320875   1.061783    -3.13   0.010    -5.657843   -.9839062
         chinatrend |   -132.421   204.9937    -0.65   0.532    -583.6091    318.7671
        francetrend |  -4.189523   1.910728    -2.19   0.051    -8.395007      .01596
         italytrend |  -5.502427   5.826805    -0.94   0.365    -18.32714    7.322285
         japantrend |   41.90037   8.581898     4.88   0.000     23.01174      60.789
   netherlandstrend |  -1.608678    1.20494    -1.34   0.209    -4.260732    1.043376
         spaintrend |  -2.091568   .0794229   -26.33   0.000    -2.266377    -1.91676
        swedentrend |  -2.210819   5.772664    -0.38   0.709    -14.91637    10.49473
           usatrend |   8.786556   19.63012     0.45   0.663    -34.41905    51.99217
            uktrend |  -4.780244   1.346831    -3.55   0.005    -7.744599   -1.815888
          ottotrend |   1.205698   .6153121     1.96   0.076    -.1485949    2.559991
              _cons |   3822.527   8335.443     0.46   0.655    -14523.66    22168.71
--------------------+----------------------------------------------------------------
            sigma_u |  78424.363
            sigma_e |  1057.3983
                rho |  .99981824   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Prussia/Germany", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       412
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.3652                         Obs per group: min =         5
       between = 0.7483                                        avg =      34.3
       overall = 0.3459                                        max =       109

                                                F(7,11)            =  36744.19
corr(u_i, Xb)  = -0.9343                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 12 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   30226.05   4751.755     6.36   0.000      19767.5    40684.59
firstcruise_lib |  -3332.984   778.5518    -4.28   0.001    -5046.565   -1619.403
         popul1 |   .0120775   .0022457     5.38   0.000     .0071347    .0170203
        gdppcip |   .2593529   .1409208     1.84   0.093    -.0508117    .5695174
   literacy_qrt |   18.17525   92.23152     0.20   0.847     -184.825    221.1754
      democracy |   -359.557   484.3716    -0.74   0.473    -1425.652    706.5377
           year |  -2.063197   1.288488    -1.60   0.138     -4.89914    .7727456
          _cons |   2642.867   2068.791     1.28   0.228    -1910.511    7196.244
----------------+----------------------------------------------------------------
        sigma_u |  2911.7966
        sigma_e |  1194.8948
            rho |  .85587265   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swede
> ntrend usatrend uktrend ottotrend if waryear==1 & country~="Prussia/Germany", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       412
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.3818                         Obs per group: min =         5
       between = 0.0030                                        avg =      34.3
       overall = 0.0350                                        max =       109

                                                F(6,11)            =         .
corr(u_i, Xb)  = -0.9989                        Prob > F           =         .

                                    (Std. Err. adjusted for 12 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   29958.01   3017.662     9.93   0.000     23316.18    36599.83
    firstcruise_lib |  -3076.401   1078.727    -2.85   0.016    -5450.662   -702.1403
             popul1 |    .011653   .0050599     2.30   0.042     .0005163    .0227897
            gdppcip |   .1903552   .1632588     1.17   0.268     -.168975    .5496853
       literacy_qrt |   38.03292   202.1791     0.19   0.854    -406.9603    483.0261
          democracy |  -42.25943   355.3768    -0.12   0.907    -824.4385    739.9197
austriahungarytrend |  -1.211346   1.468521    -0.82   0.427    -4.443539    2.020846
         chinatrend |  -49.16313   98.03677    -0.50   0.626    -264.9406    166.6143
        francetrend |  -2.464939   2.173827    -1.13   0.281    -7.249501    2.319622
         italytrend |   .5200759   7.372361     0.07   0.945    -15.70638    16.74653
         japantrend |    51.2674   6.481239     7.91   0.000     37.00229    65.53251
   netherlandstrend |   -1.00032    1.33208    -0.75   0.468    -3.932208    1.931568
         spaintrend |   -2.04257   .0274904   -74.30   0.000    -2.103076   -1.982064
        swedentrend |  -.9345871   5.564527    -0.17   0.870    -13.18203    11.31285
           usatrend |    21.7039   13.41498     1.62   0.134    -7.822271    51.23006
            uktrend |  -2.256114   2.131639    -1.06   0.313    -6.947821    2.435592
          ottotrend |   .9705496   .2888745     3.36   0.006      .334741    1.606358
              _cons |  -3812.243   2195.911    -1.74   0.110    -8645.411    1020.925
--------------------+----------------------------------------------------------------
            sigma_u |  43484.521
            sigma_e |  1194.4661
                rho |  .99924604   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany", fe cluster(count
> ryno);

Fixed-effects (within) regression               Number of obs      =       373
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.3034                         Obs per group: min =         5
       between = 0.8404                                        avg =      33.9
       overall = 0.4186                                        max =       109

                                                F(7,10)            = 334150.66
corr(u_i, Xb)  = -0.9564                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   24216.72   7245.367     3.34   0.007      8073.04    40360.41
firstcruise_lib |  -3631.911   671.4316    -5.41   0.000    -5127.954   -2135.868
         popul1 |   .0109787   .0013101     8.38   0.000     .0080596    .0138977
        gdppcip |   .2716942   .1380482     1.97   0.077    -.0358964    .5792847
   literacy_qrt |    53.1904   103.1623     0.52   0.617    -176.6695    283.0503
      democracy |  -251.6515   565.7902    -0.44   0.666    -1512.311    1009.008
           year |  -1.994091   1.380843    -1.44   0.179      -5.0708    1.082619
          _cons |     2535.1   2161.353     1.17   0.268    -2280.694    7350.894
----------------+----------------------------------------------------------------
        sigma_u |  2372.9385
        sigma_e |   1031.283
            rho |  .84112877   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swede
> ntrend usatrend uktrend ottotrend if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       373
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.3462                         Obs per group: min =         5
       between = 0.5448                                        avg =      33.9
       overall = 0.1613                                        max =       109

                                                F(6,10)            =         .
corr(u_i, Xb)  = -1.0000                        Prob > F           =         .

                                    (Std. Err. adjusted for 11 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   23788.11    4986.13     4.77   0.001     12678.32     34897.9
    firstcruise_lib |  -3029.029   689.5006    -4.39   0.001    -4565.333   -1492.726
             popul1 |  -.0290771   .0420887    -0.69   0.505    -.1228565    .0647024
            gdppcip |   .2318124   .1436358     1.61   0.138     -.088228    .5518529
       literacy_qrt |   376.5148   280.9704     1.34   0.210    -249.5263    1002.556
          democracy |   109.3339   251.6162     0.43   0.673    -451.3019    669.9697
austriahungarytrend |   1.755651   3.920804     0.45   0.664    -6.980444    10.49175
         chinatrend |   538.2041   608.0847     0.89   0.397    -816.6931    1893.101
        francetrend |  -3.294013   1.720584    -1.91   0.085    -7.127713     .539686
         italytrend |  -1.503304   4.109032    -0.37   0.722     -10.6588     7.65219
         japantrend |   82.68768   31.10554     2.66   0.024     13.38022    151.9951
   netherlandstrend |  -1.179248   1.128684    -1.04   0.321    -3.694112    1.335617
         spaintrend |   -1.79079   .2596125    -6.90   0.000    -2.369242   -1.212337
        swedentrend |  -10.28486   7.755646    -1.33   0.214    -27.56552    6.995796
           usatrend |   88.64164   70.94392     1.25   0.240    -69.43126    246.7145
            uktrend |   1.229013   4.711028     0.26   0.799    -9.267812    11.72584
          ottotrend |  -.6897458   1.727386    -0.40   0.698    -4.538602     3.15911
              _cons |  -38639.61    36632.1    -1.05   0.316      -120261     42981.8
--------------------+----------------------------------------------------------------
            sigma_u |  309372.23
            sigma_e |  1013.4361
                rho |  .99998927   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Russia/Soviet Union", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       404
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.2044                         Obs per group: min =         5
       between = 0.0423                                        avg =      33.7
       overall = 0.0224                                        max =       109

                                                F(7,11)            =   1241.43
corr(u_i, Xb)  = -0.8681                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 12 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |    .282039   .0908626     3.10   0.010     .0820519    .4820262
firstcruise_lib |   -.035532   .0088865    -4.00   0.002    -.0550909    -.015973
         popul1 |   7.82e-08   3.27e-08     2.39   0.036     6.28e-09    1.50e-07
        gdppcip |   1.46e-06   1.48e-06     0.98   0.346    -1.81e-06    4.73e-06
   literacy_qrt |    .001679   .0038122     0.44   0.668    -.0067117    .0100697
      democracy |   .0098647   .0042463     2.32   0.040     .0005187    .0192107
           year |   1.06e-06   .0000207     0.05   0.960    -.0000445    .0000466
          _cons |    .000367   .0316958     0.01   0.991     -.069395    .0701289
----------------+----------------------------------------------------------------
        sigma_u |  .04417638
        sigma_e |   .0215892
            rho |  .80721185   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swedentre
> nd usatrend uktrend ottotrend if waryear==1 & country~="Russia/Soviet Union", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       404
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.2308                         Obs per group: min =         5
       between = 0.1919                                        avg =      33.7
       overall = 0.0034                                        max =       109

                                                F(6,11)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 12 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .3403499   .1470762     2.31   0.041     .0166374    .6640624
    firstcruise_lib |  -.0352837   .0097007    -3.64   0.004    -.0566348   -.0139327
             popul1 |  -4.77e-08   2.45e-07    -0.19   0.849    -5.88e-07    4.92e-07
            gdppcip |   8.60e-07   1.30e-06     0.66   0.522    -2.00e-06    3.72e-06
       literacy_qrt |   .0045639   .0068368     0.67   0.518    -.0104838    .0196117
          democracy |   .0106537   .0018789     5.67   0.000     .0065181    .0147892
austriahungarytrend |  -.0000229   .0000365    -0.63   0.544    -.0001033    .0000575
         chinatrend |   .0014235   .0031371     0.45   0.659    -.0054811    .0083282
        francetrend |  -2.38e-06    .000057    -0.04   0.967    -.0001279    .0001231
         italytrend |    -.00002   .0002016    -0.10   0.923    -.0004638    .0004238
         japantrend |   .0008648    .000194     4.46   0.001     .0004379    .0012917
   netherlandstrend |   .0002379   .0000112    21.26   0.000     .0002133    .0002625
         spaintrend |  -.0002401   1.57e-06  -153.16   0.000    -.0002436   -.0002367
        swedentrend |  -.0003068    .000188    -1.63   0.131    -.0007206     .000107
           usatrend |   .0006896   .0005678     1.21   0.250      -.00056    .0019392
            uktrend |  -.0000133   .0000238    -0.56   0.588    -.0000657    .0000392
          ottotrend |   .0000336   9.39e-06     3.58   0.004     .0000129    .0000543
              _cons |  -.1888112   .1524708    -1.24   0.241    -.5243972    .1467749
--------------------+----------------------------------------------------------------
            sigma_u |  .99793914
            sigma_e |  .02150945
                rho |  .99953565   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Prussia/Germany", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       412
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.1785                         Obs per group: min =         5
       between = 0.0137                                        avg =      34.3
       overall = 0.0553                                        max =       109

                                                F(7,11)            =   6713.15
corr(u_i, Xb)  = -0.6947                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 12 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .1315005   .0347854     3.78   0.003     .0549384    .2080627
firstcruise_lib |  -.0274268    .010824    -2.53   0.028    -.0512504   -.0036033
         popul1 |   2.67e-08   4.07e-08     0.66   0.525    -6.29e-08    1.16e-07
        gdppcip |   7.06e-07   1.62e-06     0.44   0.671    -2.86e-06    4.27e-06
   literacy_qrt |   .0023948   .0033633     0.71   0.491    -.0050077    .0097974
      democracy |   .0158926   .0043292     3.67   0.004     .0063641     .025421
           year |   7.60e-06   .0000171     0.44   0.665      -.00003    .0000452
          _cons |    -.00753   .0260025    -0.29   0.778    -.0647611     .049701
----------------+----------------------------------------------------------------
        sigma_u |  .02874777
        sigma_e |  .02101955
            rho |  .65163063   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swedentre
> nd usatrend uktrend ottotrend if waryear==1 & country~="Prussia/Germany", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       412
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.2171                         Obs per group: min =         5
       between = 0.1568                                        avg =      34.3
       overall = 0.0030                                        max =       109

                                                F(6,11)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 12 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .2472842   .0795049     3.11   0.010     .0722951    .4222732
    firstcruise_lib |   -.027484   .0100885    -2.72   0.020    -.0496887   -.0052794
             popul1 |  -1.37e-07   1.33e-07    -1.03   0.324    -4.29e-07    1.55e-07
            gdppcip |  -6.13e-09   1.47e-06    -0.00   0.997    -3.24e-06    3.22e-06
       literacy_qrt |   .0049244   .0053328     0.92   0.376     -.006813    .0166619
          democracy |   .0143096   .0018328     7.81   0.000     .0102757    .0183436
austriahungarytrend |  -3.35e-06   .0000361    -0.09   0.928    -.0000827     .000076
         chinatrend |    .002539   .0016184     1.57   0.145     -.001023     .006101
        francetrend |   .0000153   .0000467     0.33   0.750    -.0000875     .000118
         italytrend |   .0000303   .0001763     0.17   0.867    -.0003577    .0004183
         japantrend |   .0010098    .000105     9.62   0.000     .0007788    .0012408
   netherlandstrend |   .0002454   .0000123    19.94   0.000     .0002183    .0002725
         spaintrend |  -.0002395   8.67e-07  -276.31   0.000    -.0002414   -.0002376
        swedentrend |  -.0003162   .0001466    -2.16   0.054     -.000639    6.52e-06
           usatrend |   .0008307   .0003824     2.17   0.053     -.000011    .0016725
            uktrend |   .0000152   .0000257     0.59   0.565    -.0000413    .0000717
          ottotrend |   .0000307   4.94e-06     6.21   0.000     .0000198    .0000416
              _cons |  -.2749555   .0742975    -3.70   0.003    -.4384831   -.1114278
--------------------+----------------------------------------------------------------
            sigma_u |  1.5320199
            sigma_e |  .02078529
                rho |  .99981596   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany", fe cluster(countryno
> );

Fixed-effects (within) regression               Number of obs      =       373
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.1849                         Obs per group: min =         5
       between = 0.0298                                        avg =      33.9
       overall = 0.0308                                        max =       109

                                                F(7,10)            =   1952.24
corr(u_i, Xb)  = -0.8337                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 11 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2080496   .0513758     4.05   0.002     .0935772    .3225221
firstcruise_lib |  -.0335981    .010664    -3.15   0.010     -.057359   -.0098372
         popul1 |   6.34e-08   3.76e-08     1.69   0.123    -2.04e-08    1.47e-07
        gdppcip |   1.19e-06   1.60e-06     0.74   0.475    -2.38e-06    4.76e-06
   literacy_qrt |   .0031679   .0041014     0.77   0.458    -.0059707    .0123064
      democracy |    .011921   .0045703     2.61   0.026     .0017379    .0221042
           year |  -5.44e-06   .0000223    -0.24   0.812    -.0000551    .0000443
          _cons |   .0099545   .0342322     0.29   0.777    -.0663195    .0862285
----------------+----------------------------------------------------------------
        sigma_u |  .03821503
        sigma_e |  .02163503
            rho |  .75728097   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swedentre
> nd usatrend uktrend ottotrend if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       373
Group variable: countryno                       Number of groups   =        11

R-sq:  within  = 0.2418                         Obs per group: min =         5
       between = 0.1458                                        avg =      33.9
       overall = 0.0071                                        max =       109

                                                F(6,10)            =         .
corr(u_i, Xb)  = -1.0000                        Prob > F           =         .

                                    (Std. Err. adjusted for 11 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .1602103   .1002066     1.60   0.141    -.0630639    .3834846
    firstcruise_lib |  -.0214121    .016855    -1.27   0.233    -.0589675    .0161432
             popul1 |  -9.12e-07   7.36e-07    -1.24   0.244    -2.55e-06    7.29e-07
            gdppcip |   4.58e-07   1.34e-06     0.34   0.740    -2.53e-06    3.45e-06
       literacy_qrt |   .0115585   .0080851     1.43   0.183    -.0064563    .0295733
          democracy |   .0171241   .0027247     6.28   0.000     .0110531    .0231952
austriahungarytrend |   .0000511   .0000524     0.98   0.352    -.0000656    .0001679
         chinatrend |   .0134942   .0101535     1.33   0.213    -.0091291    .0361176
        francetrend |  -3.74e-06   .0000309    -0.12   0.906    -.0000726    .0000651
         italytrend |  -.0000153   .0001378    -0.11   0.914    -.0003224    .0002918
         japantrend |   .0016045   .0005736     2.80   0.019     .0003265    .0028825
   netherlandstrend |   .0002446   .0000121    20.28   0.000     .0002178    .0002715
         spaintrend |  -.0002347   4.61e-06   -50.88   0.000     -.000245   -.0002244
        swedentrend |  -.0004993   .0002224    -2.25   0.049    -.0009948   -3.78e-06
           usatrend |   .0021052   .0013119     1.60   0.140    -.0008178    .0050282
            uktrend |   .0000815   .0000767     1.06   0.313    -.0000895    .0002525
          ottotrend |  -6.58e-07   .0000292    -0.02   0.982    -.0000658    .0000645
              _cons |  -.9506632   .6180465    -1.54   0.155    -2.327757    .4264302
--------------------+----------------------------------------------------------------
            sigma_u |  7.7434149
            sigma_e |  .02116647
                rho |  .99999253   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 and 3 dropping France and dropping France, Russia, and Prussi/Germany**/
> xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="France", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       362
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.4941                         Obs per group: min =         5
       between = 0.6114                                        avg =      30.2
       overall = 0.3195                                        max =       109

                                                F(6,11)            =         .
corr(u_i, Xb)  = -0.9397                        Prob > F           =         .

                                (Std. Err. adjusted for 12 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   40495.05    3148.54    12.86   0.000     33565.16    47424.94
firstcruise_lib |  -3964.054   486.6216    -8.15   0.000    -5035.101   -2893.007
         popul1 |   .0103872   .0018684     5.56   0.000     .0062748    .0144995
        gdppcip |    .458595   .0759572     6.04   0.000     .2914142    .6257757
   literacy_qrt |  -135.3306   107.7196    -1.26   0.235    -372.4198    101.7587
      democracy |  -1617.619   417.6237    -3.87   0.003    -2536.802   -698.4354
           year |  -1.756976    1.37145    -1.28   0.227    -4.775516    1.261564
          _cons |   1837.946   2247.744     0.82   0.431    -3109.306    6785.197
----------------+----------------------------------------------------------------
        sigma_u |  3807.0945
        sigma_e |  1212.4245
            rho |  .90791916   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swede
> ntrend usatrend uktrend ottotrend if waryear==1 & country~="France", fe cluster(countryno);
note: francetrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       362
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.4998                         Obs per group: min =         5
       between = 0.0138                                        avg =      30.2
       overall = 0.0082                                        max =       109

                                                F(5,11)            =         .
corr(u_i, Xb)  = -0.9957                        Prob > F           =         .

                                    (Std. Err. adjusted for 12 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   37980.06   4055.844     9.36   0.000     29053.21    46906.91
    firstcruise_lib |  -3818.028   585.3664    -6.52   0.000    -5106.411   -2529.646
             popul1 |   .0110699   .0051436     2.15   0.054     -.000251    .0223908
            gdppcip |   .4508368   .1655682     2.72   0.020     .0864237      .81525
       literacy_qrt |  -185.2401   174.1504    -1.06   0.310    -568.5426    198.0624
          democracy |  -1179.674   615.0537    -1.92   0.081    -2533.398    174.0498
austriahungarytrend |  -.5297483   1.479246    -0.36   0.727    -3.785546     2.72605
         chinatrend |  -18.24318   82.66468    -0.22   0.829    -200.1869    163.7006
        francetrend |          0  (omitted)
         italytrend |   1.948345   6.623108     0.29   0.774    -12.62902    16.52571
         japantrend |    37.8361   5.399779     7.01   0.000     25.95127    49.72093
   netherlandstrend |  -3.141009   1.344857    -2.34   0.039    -6.101019   -.1809988
         spaintrend |  -2.053969   .0245396   -83.70   0.000    -2.107981   -1.999958
        swedentrend |   5.059899   4.781231     1.06   0.313    -5.463519    15.58332
           usatrend |    -8.5151   21.36046    -0.40   0.698    -55.52915    38.49896
            uktrend |  -3.231596   1.453223    -2.22   0.048    -6.430118    -.033074
          ottotrend |   .7518649   .3178149     2.37   0.037      .052359    1.451371
              _cons |  -1133.737   3064.444    -0.37   0.718    -7878.533    5611.059
--------------------+----------------------------------------------------------------
            sigma_u |  24098.411
            sigma_e |  1221.7256
                rho |  .99743637   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="France", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       362
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.2169                         Obs per group: min =         5
       between = 0.0550                                        avg =      30.2
       overall = 0.0143                                        max =       109

                                                F(6,11)            =         .
corr(u_i, Xb)  = -0.8555                        Prob > F           =         .

                                (Std. Err. adjusted for 12 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2334734   .0739292     3.16   0.009     .0707562    .3961906
firstcruise_lib |  -.0383723   .0094846    -4.05   0.002    -.0592478   -.0174967
         popul1 |   5.37e-08   4.88e-08     1.10   0.294    -5.36e-08    1.61e-07
        gdppcip |   2.97e-06   8.23e-07     3.61   0.004     1.16e-06    4.78e-06
   literacy_qrt |  -.0030666   .0017596    -1.74   0.109    -.0069394    .0008062
      democracy |   .0043696   .0054664     0.80   0.441    -.0076618    .0164011
           year |   .0000203   .0000141     1.44   0.177    -.0000107    .0000513
          _cons |  -.0248923   .0236953    -1.05   0.316    -.0770453    .0272608
----------------+----------------------------------------------------------------
        sigma_u |  .04025799
        sigma_e |  .01775921
            rho |  .83710025   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swedentre
> nd usatrend uktrend ottotrend if waryear==1 & country~="France", fe cluster(countryno);
note: francetrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       362
Group variable: countryno                       Number of groups   =        12

R-sq:  within  = 0.2428                         Obs per group: min =         5
       between = 0.1282                                        avg =      30.2
       overall = 0.0035                                        max =       109

                                                F(5,11)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 12 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .3134874   .0773849     4.05   0.002     .1431643    .4838105
    firstcruise_lib |  -.0391876   .0087994    -4.45   0.001    -.0585549   -.0198203
             popul1 |  -2.74e-08   2.84e-08    -0.96   0.356    -9.00e-08    3.52e-08
            gdppcip |   3.14e-06   1.59e-06     1.98   0.074    -3.58e-07    6.63e-06
       literacy_qrt |  -.0023452   .0025563    -0.92   0.379    -.0079717    .0032812
          democracy |   .0035918   .0059535     0.60   0.559    -.0095117    .0166954
austriahungarytrend |   .0000361   .0000196     1.84   0.092    -6.97e-06    .0000792
         chinatrend |    .001503   .0003725     4.03   0.002      .000683     .002323
        francetrend |          0  (omitted)
         italytrend |   .0002066   .0000694     2.98   0.013     .0000539    .0003593
         japantrend |   .0007777   .0000842     9.24   0.000     .0005925     .000963
   netherlandstrend |   .0002191    .000013    16.81   0.000     .0001904    .0002478
         spaintrend |  -.0002404   1.82e-07 -1322.59   0.000    -.0002408     -.00024
        swedentrend |  -.0001178   .0000698    -1.69   0.119    -.0002714    .0000357
           usatrend |   .0002573   .0003573     0.72   0.487    -.0005292    .0010438
            uktrend |   .0000162   .0000154     1.05   0.317    -.0000178    .0000502
          ottotrend |   .0000327   1.81e-06    18.05   0.000     .0000287    .0000367
              _cons |  -.1987438   .0624822    -3.18   0.009    -.3362662   -.0612213
--------------------+----------------------------------------------------------------
            sigma_u |  .92629823
            sigma_e |  .01769689
                rho |  .99963513   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany" & country~="Franc
> e", fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       292
Group variable: countryno                       Number of groups   =        10

R-sq:  within  = 0.3700                         Obs per group: min =         5
       between = 0.7386                                        avg =      29.2
       overall = 0.4298                                        max =       109

                                                F(6,9)             =         .
corr(u_i, Xb)  = -0.9769                        Prob > F           =         .

                                (Std. Err. adjusted for 10 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   37015.37   5962.189     6.21   0.000     23527.97    50502.78
firstcruise_lib |  -4194.711   273.1044   -15.36   0.000    -4812.517   -3576.906
         popul1 |   .0105531   .0020042     5.27   0.001     .0060192     .015087
        gdppcip |   .4549793   .0911576     4.99   0.001     .2487665    .6611922
   literacy_qrt |  -18.52766   122.5059    -0.15   0.883    -295.6552    258.5998
      democracy |  -1508.264   546.8393    -2.76   0.022    -2745.301   -271.2279
           year |  -2.633048   1.744372    -1.51   0.165    -6.579091    1.312994
          _cons |   2969.813   2759.792     1.08   0.310     -3273.27    9212.895
----------------+----------------------------------------------------------------
        sigma_u |  3759.0535
        sigma_e |  993.98923
            rho |  .93464863   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swede
> ntrend usatrend uktrend ottotrend if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany" & country~="France", fe cluster(countryno);
note: francetrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       292
Group variable: countryno                       Number of groups   =        10

R-sq:  within  = 0.3866                         Obs per group: min =         5
       between = 0.5166                                        avg =      29.2
       overall = 0.1711                                        max =       109

                                                F(5,9)             =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                                    (Std. Err. adjusted for 10 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   33132.34   6647.806     4.98   0.001     18093.95    48170.72
    firstcruise_lib |  -3792.108   359.4328   -10.55   0.000    -4605.201   -2979.015
             popul1 |   -.009038   .0461684    -0.20   0.849    -.1134782    .0954021
            gdppcip |   .4295362   .1935966     2.22   0.054    -.0084098    .8674821
       literacy_qrt |   141.8725   375.1773     0.38   0.714    -706.8375    990.5825
          democracy |  -786.7953   907.7648    -0.87   0.409    -2840.302    1266.711
austriahungarytrend |  -.4342413    3.84306    -0.11   0.913    -9.127847    8.259365
         chinatrend |   268.3635   653.6508     0.41   0.691    -1210.297    1747.024
        francetrend |          0  (omitted)
         italytrend |  -4.144588   7.763453    -0.53   0.606    -21.70674    13.41756
         japantrend |   55.82993   33.27719     1.68   0.128     -19.4483    131.1082
   netherlandstrend |  -2.885717   1.530755    -1.89   0.092    -6.348526    .5770924
         spaintrend |  -1.927257   .2839575    -6.79   0.000    -2.569613     -1.2849
        swedentrend |  -3.939445   10.36712    -0.38   0.713     -27.3915    19.51261
           usatrend |   31.06578   76.75115     0.40   0.695    -142.5574    204.6889
            uktrend |  -2.821518   2.919358    -0.97   0.359    -9.425565    3.782529
          ottotrend |   -.036478   1.907825    -0.02   0.985    -4.352278    4.279322
              _cons |  -22669.35   48200.29    -0.47   0.649      -131706    86367.27
--------------------+----------------------------------------------------------------
            sigma_u |  162894.41
            sigma_e |  997.25402
                rho |  .99996252   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany" & country~="France", 
> fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       292
Group variable: countryno                       Number of groups   =        10

R-sq:  within  = 0.2021                         Obs per group: min =         5
       between = 0.0681                                        avg =      29.2
       overall = 0.0085                                        max =       109

                                                F(6,9)             =         .
corr(u_i, Xb)  = -0.9184                        Prob > F           =         .

                                (Std. Err. adjusted for 10 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2782364   .0774444     3.59   0.006     .1030449    .4534279
firstcruise_lib |  -.0465111   .0104157    -4.47   0.002    -.0700732   -.0229491
         popul1 |   9.92e-08   3.94e-08     2.52   0.033     1.01e-08    1.88e-07
        gdppcip |   3.41e-06   6.78e-07     5.03   0.001     1.88e-06    4.95e-06
   literacy_qrt |  -.0019429   .0016873    -1.15   0.279    -.0057598    .0018739
      democracy |  -.0007519   .0053719    -0.14   0.892    -.0129039    .0114002
           year |   .0000118   .0000163     0.73   0.485    -.0000249    .0000486
          _cons |  -.0179297   .0266014    -0.67   0.517    -.0781063    .0422468
----------------+----------------------------------------------------------------
        sigma_u |  .05146204
        sigma_e |  .01777903
            rho |  .89337133   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend spaintrend swedentre
> nd usatrend uktrend ottotrend if waryear==1 & country~="Russia/Soviet Union" & country~="Prussia/Germany" & country~="France", fe cluster(countryno);
note: francetrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       292
Group variable: countryno                       Number of groups   =        10

R-sq:  within  = 0.2298                         Obs per group: min =         5
       between = 0.1547                                        avg =      29.2
       overall = 0.0071                                        max =       109

                                                F(5,9)             =         .
corr(u_i, Xb)  = -0.9999                        Prob > F           =         .

                                    (Std. Err. adjusted for 10 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .2010632   .0809269     2.48   0.035     .0179938    .3841326
    firstcruise_lib |  -.0381931   .0079351    -4.81   0.001    -.0561435   -.0202427
             popul1 |  -2.20e-07   3.85e-07    -0.57   0.581    -1.09e-06    6.50e-07
            gdppcip |   2.24e-06   1.55e-06     1.44   0.183    -1.27e-06    5.75e-06
       literacy_qrt |   .0014824    .003872     0.38   0.711    -.0072766    .0102415
          democracy |   .0113689    .009868     1.15   0.279    -.0109541    .0336918
austriahungarytrend |   .0000367   .0000342     1.07   0.311    -.0000407    .0001142
         chinatrend |   .0042742   .0054622     0.78   0.454    -.0080823    .0166306
        francetrend |          0  (omitted)
         italytrend |   .0001506   .0000667     2.26   0.050    -2.87e-07    .0003016
         japantrend |   .0010095   .0003275     3.08   0.013     .0002686    .0017504
   netherlandstrend |   .0002272   .0000131    17.40   0.000     .0001977    .0002568
         spaintrend |  -.0002391   2.41e-06   -99.05   0.000    -.0002446   -.0002337
        swedentrend |  -.0002228   .0001063    -2.10   0.066    -.0004632    .0000177
           usatrend |   .0007051   .0007772     0.91   0.388    -.0010531    .0024633
            uktrend |   .0000247   .0000301     0.82   0.433    -.0000434    .0000928
          ottotrend |   .0000257   .0000153     1.68   0.127    -8.92e-06    .0000603
              _cons |  -.4761892   .4348851    -1.09   0.302    -1.459968    .5075893
--------------------+----------------------------------------------------------------
            sigma_u |  2.5983207
            sigma_e |  .01776125
                rho |  .99995328   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /** Rerun Table 2 and 3 without WWI **/
> preserve;

. drop if year>=1914 & year<=1918;
(40 observations deleted)

. xtreg military1 RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       408
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4013                         Obs per group: min =         5
       between = 0.4479                                        avg =      31.4
       overall = 0.3104                                        max =       105

                                                F(5,12)            =    451.67
corr(u_i, Xb)  = -0.9536                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   50500.48   7065.323     7.15   0.000     35106.46    65894.49
firstcruise_lib |  -877.9266   148.0821    -5.93   0.000     -1200.57   -555.2833
         gt1789 |   134.3235   92.97596     1.44   0.174    -68.25369    336.9007
         gt1859 |  -449.6165   352.0862    -1.28   0.226    -1216.746    317.5136
         gt1970 |   837.4151   224.2829     3.73   0.003     348.7445    1326.086
          _cons |  -490.7573   181.1183    -2.71   0.019    -885.3802    -96.1344
----------------+----------------------------------------------------------------
        sigma_u |  3702.7145
        sigma_e |  1068.2487
            rho |    .923161   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       408
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4884                         Obs per group: min =         5
       between = 0.6911                                        avg =      31.4
       overall = 0.3993                                        max =       105

                                                F(7,12)            =   4598.17
corr(u_i, Xb)  = -0.9401                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   37846.35    5733.84     6.60   0.000     25353.38    50339.31
firstcruise_lib |  -3339.739   692.7929    -4.82   0.000    -4849.205   -1830.273
         popul1 |   .0086504   .0035711     2.42   0.032     .0008696    .0164312
        gdppcip |   .3119517   .1033177     3.02   0.011     .0868418    .5370616
   literacy_qrt |  -56.52609   176.0767    -0.32   0.754    -440.1643    327.1122
      democracy |  -1183.932   450.5038    -2.63   0.022    -2165.495   -202.3685
           year |  -1.694873   1.724037    -0.98   0.345    -5.451227    2.061481
          _cons |   2097.814   2789.379     0.75   0.467    -3979.721    8175.349
----------------+----------------------------------------------------------------
        sigma_u |  3034.9623
        sigma_e |  990.00424
            rho |  .90382707   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend rus
> siatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       408
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.5142                         Obs per group: min =         5
       between = 0.0015                                        avg =      31.4
       overall = 0.0168                                        max =       105

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9987                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   37540.21   7323.594     5.13   0.000     21583.46    53496.95
    firstcruise_lib |  -2927.841   858.8331    -3.41   0.005    -4799.077   -1056.604
             popul1 |   .0092013    .017723     0.52   0.613    -.0294139    .0478165
            gdppcip |   .2637955    .163071     1.62   0.132    -.0915058    .6190967
       literacy_qrt |  -.9288118   276.8468    -0.00   0.997    -604.1262    602.2686
          democracy |  -911.7901   462.3071    -1.97   0.072    -1919.071    95.49062
austriahungarytrend |  -.6500423   .9734018    -0.67   0.517    -2.770903    1.470818
         chinatrend |   -26.0314   249.5935    -0.10   0.919    -569.8488     517.786
        francetrend |   -3.97217   3.126174    -1.27   0.228    -10.78352    2.839179
         italytrend |   6.594434   9.233473     0.71   0.489    -13.52358    26.71244
         japantrend |   72.76421   10.21662     7.12   0.000     50.50411    95.02431
   netherlandstrend |  -1.594761   1.303612    -1.22   0.245    -4.435088    1.245566
       germanytrend |   5.703168   5.222897     1.09   0.296    -5.676546    17.08288
        russiatrend |  -5.949723   9.691056    -0.61   0.551    -27.06472    15.16528
         spaintrend |   -2.03151   .1056445   -19.23   0.000     -2.26169    -1.80133
        swedentrend |   .0946206    7.64742     0.01   0.990    -16.56768    16.75692
           usatrend |   -2.16955         25    -0.09   0.932    -56.63986    52.30076
            uktrend |  -2.084553   2.093762    -1.00   0.339    -6.646468    2.477363
          ottotrend |   .8174011    .783669     1.04   0.317    -.8900669    2.524869
              _cons |  -1801.533   11732.35    -0.15   0.881    -27364.14    23761.07
--------------------+----------------------------------------------------------------
            sigma_u |  42766.438
            sigma_e |  980.03882
                rho |  .99947513   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       408
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1385                         Obs per group: min =         5
       between = 0.0061                                        avg =      31.4
       overall = 0.0219                                        max =       105

                                                F(5,12)            =  40135.63
corr(u_i, Xb)  = -0.8213                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .2566326   .0784796     3.27   0.007     .0856403    .4276249
firstcruise_lib |  -.0142256    .001548    -9.19   0.000    -.0175984   -.0108529
         gt1789 |    .003066   .0019926     1.54   0.150    -.0012754    .0074074
         gt1859 |   .0014027   .0042256     0.33   0.746     -.007804    .0106095
         gt1970 |   .0022869   .0034836     0.66   0.524    -.0053031     .009877
          _cons |   .0103823    .001756     5.91   0.000     .0065563    .0142084
----------------+----------------------------------------------------------------
        sigma_u |  .03040381
        sigma_e |  .01550672
            rho |  .79357149   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       408
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1831                         Obs per group: min =         5
       between = 0.0401                                        avg =      31.4
       overall = 0.0234                                        max =       105

                                                F(7,12)            =    102.44
corr(u_i, Xb)  = -0.7998                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .1950466   .0727034     2.68   0.020     .0366395    .3534538
firstcruise_lib |  -.0349711   .0098481    -3.55   0.004    -.0564283    -.013514
         popul1 |   3.68e-08   5.06e-08     0.73   0.480    -7.33e-08    1.47e-07
        gdppcip |   2.33e-06   7.45e-07     3.13   0.009     7.07e-07    3.95e-06
   literacy_qrt |   -.001977   .0019517    -1.01   0.331    -.0062294    .0022754
      democracy |  -.0035409   .0025918    -1.37   0.197    -.0091879    .0021062
           year |   .0000278   .0000186     1.50   0.161    -.0000127    .0000684
          _cons |  -.0375017   .0311961    -1.20   0.253    -.1054723    .0304689
----------------+----------------------------------------------------------------
        sigma_u |  .03175109
        sigma_e |  .01513898
            rho |   .8147701   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiat
> rend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       408
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.2330                         Obs per group: min =         5
       between = 0.0216                                        avg =      31.4
       overall = 0.0028                                        max =       105

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   .2741162   .0393911     6.96   0.000     .1882903     .359942
    firstcruise_lib |  -.0334324   .0098764    -3.39   0.005    -.0549513   -.0119135
             popul1 |   2.32e-08   1.80e-07     0.13   0.900    -3.68e-07    4.15e-07
            gdppcip |   1.93e-06   1.04e-06     1.86   0.088    -3.34e-07    4.19e-06
       literacy_qrt |  -.0021812   .0029398    -0.74   0.472    -.0085864     .004224
          democracy |  -.0065516   .0021622    -3.03   0.010    -.0112626   -.0018407
austriahungarytrend |   .0000208   6.91e-06     3.02   0.011     5.79e-06    .0000359
         chinatrend |   .0006089    .002384     0.26   0.803    -.0045854    .0058031
        francetrend |   .0000412   .0000219     1.89   0.084    -6.42e-06    .0000888
         italytrend |   .0004469   .0000668     6.69   0.000     .0003013    .0005925
         japantrend |   .0011886   .0001428     8.32   0.000     .0008774    .0014999
   netherlandstrend |   .0002288   8.68e-06    26.36   0.000     .0002099    .0002477
       germanytrend |   .0000355   .0000714     0.50   0.628    -.0001201    .0001911
        russiatrend |  -.0000698    .000123    -0.57   0.581    -.0003378    .0001982
         spaintrend |  -.0002406   1.13e-06  -212.68   0.000    -.0002431   -.0002382
        swedentrend |  -.0001216   .0000809    -1.50   0.159    -.0002979    .0000546
           usatrend |   .0001565   .0003304     0.47   0.644    -.0005635    .0008764
            uktrend |   .0000529   .0000219     2.41   0.033     5.13e-06    .0001007
          ottotrend |   .0000356   7.12e-06     5.01   0.000     .0000201    .0000511
              _cons |    -.16026   .1427599    -1.12   0.284    -.4713072    .1507872
--------------------+----------------------------------------------------------------
            sigma_u |  .72852575
            sigma_e |  .01490217
                rho |  .99958176   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. restore;

. /** Rerun Table 2 and 3 without WWI & WWII **/
> preserve;

. drop if (year>=1914 & year<=1918) | (year>=1939 & year<=1945);
(87 observations deleted)

. xtreg military1 RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       366
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.5153                         Obs per group: min =         5
       between = 0.3607                                        avg =      28.2
       overall = 0.4961                                        max =        98

                                                F(5,12)            =    630.71
corr(u_i, Xb)  = -0.8383                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   16705.67    1750.09     9.55   0.000     12892.56    20518.79
firstcruise_lib |   1193.029    333.868     3.57   0.004     465.5932    1920.465
         gt1789 |   201.9695   40.33793     5.01   0.000     114.0807    289.8583
         gt1859 |  -164.6645   84.97659    -1.94   0.077    -349.8126    20.48361
         gt1970 |  -709.1461   481.8637    -1.47   0.167    -1759.037    340.7446
          _cons |   31.13996   46.50346     0.67   0.516    -70.18237    132.4623
----------------+----------------------------------------------------------------
        sigma_u |  1308.0474
        sigma_e |  310.39911
            rho |  .94669081   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       366
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.5137                         Obs per group: min =         5
       between = 0.7644                                        avg =      28.2
       overall = 0.6896                                        max =        98

                                                F(7,12)            =   1944.88
corr(u_i, Xb)  = -0.8632                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   14357.08    2513.15     5.71   0.000     8881.398    19832.77
firstcruise_lib |   484.4419   723.1033     0.67   0.516    -1091.065    2059.949
         popul1 |   .0029767   .0026514     1.12   0.284    -.0028001    .0087536
        gdppcip |  -.0189035   .0792602    -0.24   0.816    -.1915966    .1537897
   literacy_qrt |   -31.0169   61.66088    -0.50   0.624    -165.3644    103.3306
      democracy |  -190.4903   281.7579    -0.68   0.512     -804.388    423.4075
           year |   1.454972   .8542004     1.70   0.114    -.4061709    3.316115
          _cons |  -2447.257   1325.695    -1.85   0.090    -5335.699     441.185
----------------+----------------------------------------------------------------
        sigma_u |  851.13255
        sigma_e |  311.81947
            rho |  .88166441   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend rus
> siatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       366
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.6298                         Obs per group: min =         5
       between = 0.1526                                        avg =      28.2
       overall = 0.0004                                        max =        98

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9993                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   13366.15   2783.351     4.80   0.000     7301.745    19430.55
    firstcruise_lib |   759.9285   780.5746     0.97   0.349    -940.7974    2460.654
             popul1 |   .0040577   .0081897     0.50   0.629    -.0137862    .0219016
            gdppcip |  -.0995028   .0545333    -1.82   0.093    -.2183206     .019315
       literacy_qrt |  -5.349034   54.18321    -0.10   0.923    -123.4041     112.706
          democracy |   98.98748   138.8029     0.71   0.489    -203.4381    401.4131
austriahungarytrend |    1.22815   .7499411     1.64   0.127    -.4058309    2.862132
         chinatrend |  -54.17523   112.2917    -0.48   0.638    -298.8377    190.4873
        francetrend |   1.504837   .6105781     2.46   0.030     .1745021    2.835173
         italytrend |   7.059125   2.341826     3.01   0.011     1.956725    12.16153
         japantrend |  -2.574797   6.760334    -0.38   0.710     -17.3043    12.15471
   netherlandstrend |   1.414609   .4516222     3.13   0.009     .4306091     2.39861
       germanytrend |   3.463535    1.15279     3.00   0.011       .95182    5.975249
        russiatrend |   2.247887   5.567359     0.40   0.693    -9.882346    14.37812
         spaintrend |  -1.978438   .0513774   -38.51   0.000     -2.09038   -1.866496
        swedentrend |   .4352846   1.493033     0.29   0.776    -2.817755    3.688324
           usatrend |   30.39725   13.39145     2.27   0.042     1.219792     59.5747
            uktrend |   1.763551   .9767019     1.81   0.096    -.3644998    3.891601
          ottotrend |   .8841305    .327889     2.70   0.019     .1697217    1.598539
              _cons |  -3365.877   6829.408    -0.49   0.631    -18245.88    11514.13
--------------------+----------------------------------------------------------------
            sigma_u |  35719.942
            sigma_e |  276.88064
                rho |  .99993992   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib gt1789 gt1859 gt1970 if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       366
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.0280                         Obs per group: min =         5
       between = 0.0326                                        avg =      28.2
       overall = 0.0003                                        max =        98

                                                F(5,12)            =     18.20
corr(u_i, Xb)  = -0.4488                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   .0675615    .031648     2.13   0.054    -.0013936    .1365165
firstcruise_lib |   .0014022    .002303     0.61   0.554    -.0036156      .00642
         gt1789 |   .0029608   .0018407     1.61   0.134    -.0010498    .0069715
         gt1859 |  -.0019322   .0015303    -1.26   0.231    -.0052664     .001402
         gt1970 |  -.0059083     .00324    -1.82   0.093    -.0129675     .001151
          _cons |   .0135908   .0011058    12.29   0.000     .0111814    .0160003
----------------+----------------------------------------------------------------
        sigma_u |  .02155227
        sigma_e |  .01019568
            rho |  .81713178   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       366
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.0387                         Obs per group: min =         5
       between = 0.3827                                        avg =      28.2
       overall = 0.0327                                        max =        98

                                                F(7,12)            =     23.52
corr(u_i, Xb)  = -0.4932                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |    .017831   .0360734     0.49   0.630    -.0607661    .0964281
firstcruise_lib |   .0032923   .0067046     0.49   0.632    -.0113158    .0179003
         popul1 |  -7.03e-09   2.22e-08    -0.32   0.757    -5.54e-08    4.14e-08
        gdppcip |  -1.03e-06   8.45e-07    -1.22   0.246    -2.87e-06    8.10e-07
   literacy_qrt |  -.0016207   .0015502    -1.05   0.316    -.0049984    .0017569
      democracy |   .0041303   .0037649     1.10   0.294    -.0040728    .0123334
           year |   .0000423   .0000127     3.34   0.006     .0000147      .00007
          _cons |  -.0548093   .0207438    -2.64   0.021    -.1000062   -.0096123
----------------+----------------------------------------------------------------
        sigma_u |   .0221497
        sigma_e |  .01016892
            rho |  .82591902   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend russiat
> rend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       366
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1151                         Obs per group: min =         5
       between = 0.1080                                        avg =      28.2
       overall = 0.0202                                        max =        98

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |    .046978   .0289384     1.62   0.130    -.0160733    .1100294
    firstcruise_lib |   .0065581   .0069315     0.95   0.363    -.0085442    .0216605
             popul1 |  -1.46e-07   1.32e-07    -1.10   0.291    -4.35e-07    1.42e-07
            gdppcip |  -1.77e-06   4.92e-07    -3.60   0.004    -2.84e-06   -6.98e-07
       literacy_qrt |   -.000171   .0014379    -0.12   0.907    -.0033039    .0029618
          democracy |   .0039107   .0020395     1.92   0.079    -.0005331    .0083545
austriahungarytrend |   .0000375   7.69e-06     4.88   0.000     .0000208    .0000543
         chinatrend |   .0018558   .0018116     1.02   0.326    -.0020913    .0058029
        francetrend |   .0000697    .000011     6.33   0.000     .0000457    .0000937
         italytrend |    .000228    .000031     7.34   0.000     .0001604    .0002957
         japantrend |    .000147   .0001063     1.38   0.192    -.0000847    .0003786
   netherlandstrend |   .0002599   4.16e-06    62.42   0.000     .0002508     .000269
       germanytrend |   -.000039   9.66e-06    -4.03   0.002      -.00006   -.0000179
        russiatrend |   .0001088   .0000919     1.18   0.260    -.0000915    .0003091
         spaintrend |  -.0002394   8.32e-07  -287.80   0.000    -.0002412   -.0002376
        swedentrend |  -.0001748   .0000396    -4.42   0.001     -.000261   -.0000886
           usatrend |   .0006284   .0002294     2.74   0.018     .0001285    .0011283
            uktrend |   .0000605   .0000131     4.63   0.001      .000032    .0000889
          ottotrend |   .0000316   5.26e-06     6.02   0.000     .0000202    .0000431
              _cons |  -.2006355    .106463    -1.88   0.084    -.4325985    .0313275
--------------------+----------------------------------------------------------------
            sigma_u |  1.0184734
            sigma_e |  .00992992
                rho |  .99990495   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. restore;

. /* Rerun Table 2 and 3 with control for Neighborhood Mobilization */
> use "OSS_mobil_repl_data.dta", clear;

. sort countryno year;

. xtset countryno year;
       panel variable:  countryno (unbalanced)
        time variable:  year, 1600 to 2000
                delta:  1 unit

. xtreg military1 neighmil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       315
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.5514                         Obs per group: min =         1
       between = 0.7405                                        avg =      24.2
       overall = 0.3737                                        max =        75

                                                F(8,12)            =    634.04
corr(u_i, Xb)  = -0.9047                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
       neighmil |    .000462   .0000922     5.01   0.000     .0002611    .0006628
        RRkmip1 |      25267   6371.297     3.97   0.002     11385.13    39148.86
firstcruise_lib |  -2657.532   635.2564    -4.18   0.001    -4041.637   -1273.427
         popul1 |   .0127146   .0019377     6.56   0.000     .0084928    .0169365
        gdppcip |   .2352853   .0919546     2.56   0.025     .0349333    .4356372
   literacy_qrt |  -381.2086   213.1852    -1.79   0.099    -845.6993    83.28209
      democracy |  -183.9616   396.3268    -0.46   0.651    -1047.484    679.5604
           year |  -1.390516   1.925089    -0.72   0.484    -5.584926    2.803893
          _cons |    1858.34   3173.199     0.59   0.569    -5055.466    8772.146
----------------+----------------------------------------------------------------
        sigma_u |  3144.2371
        sigma_e |  1260.2147
            rho |  .86159228   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg military1 neighmil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germany
> trend russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);
note: spaintrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       315
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.5728                         Obs per group: min =         1
       between = 0.2802                                        avg =      24.2
       overall = 0.0261                                        max =        75

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9997                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          military1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           neighmil |   .0004681   .0000959     4.88   0.000      .000259    .0006771
            RRkmip1 |   17298.03   4827.676     3.58   0.004     6779.429    27816.63
    firstcruise_lib |  -2340.812   783.2936    -2.99   0.011    -4047.462   -634.1616
             popul1 |   .0259081   .0156711     1.65   0.124    -.0082362    .0600524
            gdppcip |   .1691809   .1311042     1.29   0.221    -.1164707    .4548324
       literacy_qrt |  -378.3453   379.8013    -1.00   0.339    -1205.861    449.1708
          democracy |   187.8389   254.3565     0.74   0.474    -366.3562    742.0341
austriahungarytrend |  -5.170724   2.004275    -2.58   0.024    -9.537665   -.8037828
         chinatrend |  -233.9976   240.3039    -0.97   0.349    -757.5749    289.5796
        francetrend |  -1.362539   3.433584    -0.40   0.698    -8.843677    6.118598
         italytrend |  -.3454175    11.6719    -0.03   0.977    -25.77631    25.08547
         japantrend |   48.82185   10.38884     4.70   0.001     26.18651     71.4572
   netherlandstrend |  -1.196248   1.024497    -1.17   0.266    -3.428435     1.03594
       germanytrend |   1.965187   3.865299     0.51   0.620    -6.456577    10.38695
        russiatrend |  -8.803111   10.36775    -0.85   0.412     -31.3925    13.78628
         spaintrend |          0  (omitted)
        swedentrend |   10.54973   10.48286     1.01   0.334    -12.29046    33.38993
           usatrend |  -24.47941   26.84464    -0.91   0.380    -82.96885    34.01003
            uktrend |  -4.062126   1.610756    -2.52   0.027    -7.571661   -.5525915
          ottotrend |   .4878608   .6441751     0.76   0.463    -.9156763    1.891398
              _cons |      12009   14535.65     0.83   0.425    -19661.47    43679.46
--------------------+----------------------------------------------------------------
            sigma_u |  127317.32
            sigma_e |   1253.381
                rho |  .99990309   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg mobil neighmobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =       315
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.3730                         Obs per group: min =         1
       between = 0.1667                                        avg =      24.2
       overall = 0.0985                                        max =        75

                                                F(8,12)            =    101.63
corr(u_i, Xb)  = -0.6637                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
          mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
     neighmobil |   .5283597   .1241776     4.25   0.001     .2577999    .7989194
        RRkmip1 |   .1725413   .0631341     2.73   0.018     .0349839    .3100987
firstcruise_lib |  -.0173619   .0104079    -1.67   0.121    -.0400387     .005315
         popul1 |   3.21e-08   3.63e-08     0.88   0.394    -4.70e-08    1.11e-07
        gdppcip |   9.82e-07   1.33e-06     0.74   0.475    -1.92e-06    3.88e-06
   literacy_qrt |   -.004999   .0035001    -1.43   0.179     -.012625     .002627
      democracy |   .0109587   .0065838     1.66   0.122    -.0033861    .0253036
           year |   .0000235   .0000353     0.67   0.518    -.0000534    .0001005
          _cons |  -.0310933   .0584162    -0.53   0.604    -.1583713    .0961848
----------------+----------------------------------------------------------------
        sigma_u |  .03615279
        sigma_e |  .02131899
            rho |  .74198511   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg mobil neighmobil RRkmip1 firstcruise_lib popul1 gdppcip literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytr
> end russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);
note: spaintrend omitted because of collinearity

Fixed-effects (within) regression               Number of obs      =       315
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4038                         Obs per group: min =         1
       between = 0.1372                                        avg =      24.2
       overall = 0.0064                                        max =        75

                                                F(7,12)            =         .
corr(u_i, Xb)  = -0.9996                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
              mobil |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         neighmobil |   .5413726   .1290356     4.20   0.001     .2602281    .8225171
            RRkmip1 |   .1578992   .0643918     2.45   0.030     .0176015     .298197
    firstcruise_lib |  -.0180616   .0097724    -1.85   0.089    -.0393539    .0032306
             popul1 |  -8.89e-08   2.09e-07    -0.43   0.678    -5.45e-07    3.67e-07
            gdppcip |   7.23e-07   1.28e-06     0.57   0.582    -2.06e-06    3.50e-06
       literacy_qrt |  -.0036468   .0052509    -0.69   0.501    -.0150876     .007794
          democracy |    .009215   .0045695     2.02   0.067     -.000741    .0191711
austriahungarytrend |  -.0000294    .000049    -0.60   0.560    -.0001361    .0000774
         chinatrend |   .0021471   .0028948     0.74   0.473      -.00416    .0084542
        francetrend |   .0000875   .0000512     1.71   0.113    -.0000241    .0001991
         italytrend |  -.0000293   .0001864    -0.16   0.878    -.0004355    .0003769
         japantrend |   .0010329   .0002009     5.14   0.000     .0005953    .0014706
   netherlandstrend |   .0003798   .0000124    30.61   0.000     .0003527    .0004068
       germanytrend |   .0001081   .0000693     1.56   0.145    -.0000429    .0002591
        russiatrend |    .000087   .0001454     0.60   0.561    -.0002299    .0004039
         spaintrend |          0  (omitted)
        swedentrend |  -.0000805   .0001444    -0.56   0.587    -.0003952    .0002342
           usatrend |   .0004274   .0004384     0.97   0.349    -.0005279    .0013826
            uktrend |   .0000155   .0000357     0.43   0.673    -.0000623    .0000932
          ottotrend |    -.00009   .0000337    -2.67   0.020    -.0001635   -.0000165
              _cons |  -.3171779   .2119162    -1.50   0.160    -.7789037    .1445479
--------------------+----------------------------------------------------------------
            sigma_u |  1.2260526
            sigma_e |  .02118847
                rho |  .99970143   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. /***************
> Replication of Analyses in Online Appendix
> *****************/
> 
> /******
> * Figures A-1 and A-2
> *******/
> 
> twoway (connected military1 year if country=="AustriaHungary", yaxis(1) yscale(r(0 15000) axis(1)) ytitle("Military Size, Thousands",axis(1)) msymbol(O)) (connected mobil year 
> if country=="AustriaHungary", yaxis(2) yscale(r(0 0.2) axis(2)) ytitle("Mobilization",axis(2)) msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Milit
> ary Mobilization in Austria Hungary) graphregion(fcolor(white)) legend( order(1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel1,replace;
(file mobpanel1.gph saved)

. more;

. twoway (connected military1 year if country=="China", yaxis(1) ytitle("Military Size, Thousands",axis(1)) msymbol(O)) (connected mobil year if country=="China", yaxis(2) ytitle
> ("Mobilization",axis(2)) msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in China) graphregion(fcolor(white)) legend( order(1 
> 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel2,replace;
(file mobpanel2.gph saved)

. more;

. twoway (connected military1 year if country=="France", yaxis(1) ytitle("Military Size, Thousands",axis(1)) msymbol(O)) (connected mobil year if country=="France", yaxis(2) ytit
> le("Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in France) graphregion(fcolor(white)) legend( order(
> 1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel3,replace;
(file mobpanel3.gph saved)

. more;

. twoway (connected military1 year if country=="Italy", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Italy", yaxis(2) ytitle(
> "Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Italy) graphregion(fcolor(white)) legend( order(1 2)
>  lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel4,replace;
(file mobpanel4.gph saved)

. more;

. twoway (connected military1 year if country=="Japan", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Japan", yaxis(2) ytitle(
> "Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Japan) graphregion(fcolor(white)) legend( order(1 2)
>  lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel5,replace;
(file mobpanel5.gph saved)

. more;

. twoway (connected military1 year if country=="Netherlands", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Netherlands", yaxi
> s(2) ytitle("Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Netherlands) graphregion(fcolor(white)) 
> legend( order(1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel6,replace;
(file mobpanel6.gph saved)

. more;

. graph combine mobpanel1.gph mobpanel2.gph mobpanel3.gph mobpanel4.gph mobpanel5.gph mobpanel6.gph,  col(2) ycommon graphregion(fcolor(white) )  altshrink title("Mobilization in
>  Great Powers, 1600-2000") subtitle("Military Size and Mobilization Rates") xsize(6.5) ysize(8.5);

. graph save FigureA1,replace;
(file FigureA1.gph saved)

. twoway (connected military1 year if country=="Ottoman", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Ottoman", yaxis(2) yti
> tle("Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Ottoman Empire) graphregion(fcolor(white)) legen
> d( order(1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel13,replace;
(file mobpanel13.gph saved)

. more;

. twoway (connected military1 year if country=="Prussia/Germany", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Prussia/German
> y", yaxis(2) ytitle("Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Prussia/Germany) graphregion(fco
> lor(white)) legend( order(1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel7,replace;
(file mobpanel7.gph saved)

. more;

. twoway (connected military1 year if country=="Russia/Soviet Union", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Russia/Sov
> iet Union", yaxis(2) ytitle("Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Russia/Soviet Union) gra
> phregion(fcolor(white)) legend( order(1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel8,replace;
(file mobpanel8.gph saved)

. more;

. twoway (connected military1 year if country=="Spain", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Spain", yaxis(2) ytitle(
> "Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Spain) graphregion(fcolor(white)) legend( order(1 2)
>  lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel9,replace;
(file mobpanel9.gph saved)

. more;

. twoway (connected military1 year if country=="Sweden", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="Sweden", yaxis(2) ytitl
> e("Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in Sweden) graphregion(fcolor(white)) legend( order(1
>  2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel10,replace;
(file mobpanel10.gph saved)

. more;

. twoway (connected military1 year if country=="United Kingdom", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="United Kingdom"
> , yaxis(2) ytitle("Mobilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in United Kingdom) graphregion(fcolor
> (white)) legend( order(1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel11,replace;
(file mobpanel11.gph saved)

. more;

. twoway (connected military1 year if country=="USA", yaxis(1) ytitle("Military Size, Thousands",axis(1))msymbol(O)) (connected mobil year if country=="USA", yaxis(2) ytitle("Mob
> ilization",axis(2))msymbol(Dh)), xscale(r(1600 2000)) xlabel(1600(100)2000) xtitle(Year) title(Military Mobilization in United States) graphregion(fcolor(white)) legend( order(
> 1 2) lab(1 "Military Size") lab(2 "Military Mobilization"));

.  graph save mobpanel12,replace;
(file mobpanel12.gph saved)

. more;

. graph combine mobpanel13.gph mobpanel7.gph mobpanel8.gph mobpanel9.gph mobpanel10.gph mobpanel11.gph mobpanel12.gph,  col(2) ycommon graphregion(fcolor(white) )  altshrink titl
> e("Mobilization in Great Powers, 1600-2000") subtitle("Military Size and Mobilization Rates") xsize(6.5) ysize(8.5);

. graph save FigureA2,replace;
(file FigureA2.gph saved)

. /******
> * Table A-2
> *******/
> xtreg conscription RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =      1046
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.1908                         Obs per group: min =         7
       between = 0.0853                                        avg =      80.5
       overall = 0.2205                                        max =       178

                                                F(7,12)            =     71.01
corr(u_i, Xb)  = -0.1524                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
   conscription |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |  -1.259128    4.78546    -0.26   0.797    -11.68575    9.167494
firstcruise_lib |  -.1945838    .439328    -0.44   0.666    -1.151797    .7626297
         popul2 |   1.418358    2.19735     0.65   0.531    -3.369256    6.205971
       gdppcip2 |  -.0192575   .0262033    -0.73   0.477    -.0763496    .0378346
   literacy_qrt |  -.1272625    .165656    -0.77   0.457    -.4881959    .2336709
      democracy |    .292908   .2174001     1.35   0.203    -.1807662    .7665821
           year |   .0029698   .0014785     2.01   0.068    -.0002514    .0061911
          _cons |  -4.455267   2.407001    -1.85   0.089    -9.699672    .7891377
----------------+----------------------------------------------------------------
        sigma_u |  .51203122
        sigma_e |  .34813636
            rho |  .68386317   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg universal RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy year if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =      1046
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.7002                         Obs per group: min =         7
       between = 0.3125                                        avg =      80.5
       overall = 0.3704                                        max =       178

                                                F(7,12)            =    277.90
corr(u_i, Xb)  = -0.8810                        Prob > F           =    0.0000

                                (Std. Err. adjusted for 13 clusters in countryno)
---------------------------------------------------------------------------------
                |               Robust
      universal |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
        RRkmip1 |   9.292694    1.45591     6.38   0.000     6.120538    12.46485
firstcruise_lib |  -.3186324   .3445271    -0.92   0.373    -1.069293    .4320278
         popul2 |   1.585456   .8230771     1.93   0.078    -.2078753    3.378787
       gdppcip2 |   .0371198   .0118086     3.14   0.008     .0113911    .0628485
   literacy_qrt |   .0459095   .0382345     1.20   0.253    -.0373963    .1292154
      democracy |   .1282443   .0607566     2.11   0.056    -.0041329    .2606214
           year |  -.0000712   .0002264    -0.31   0.759    -.0005645    .0004221
          _cons |  -.0592166   .3391508    -0.17   0.864    -.7981626    .6797294
----------------+----------------------------------------------------------------
        sigma_u |  .91587865
        sigma_e |  .14856657
            rho |  .97436186   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. xtreg conscription RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend
>  russiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =      1046
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.4527                         Obs per group: min =         7
       between = 0.0008                                        avg =      80.5
       overall = 0.0124                                        max =       178

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9990                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
       conscription |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   2.824067   4.803684     0.59   0.568    -7.642262     13.2904
    firstcruise_lib |  -.2450632   .4048636    -0.61   0.556    -1.127185    .6370589
             popul2 |   2.038453   4.445858     0.46   0.655     -7.64824    11.72515
           gdppcip2 |  -.0284595   .0379611    -0.75   0.468    -.1111696    .0542507
       literacy_qrt |  -.1185277   .1258121    -0.94   0.365    -.3926488    .1555933
          democracy |   .0445558   .1919376     0.23   0.820    -.3736404    .4627519
austriahungarytrend |   .0052452   .0011293     4.64   0.001     .0027846    .0077059
         chinatrend |   .0108908   .0552842     0.20   0.847    -.1095631    .1313447
        francetrend |   .0042048    .001622     2.59   0.024     .0006708    .0077388
         italytrend |   .0042287   .0051967     0.81   0.432    -.0070939    .0155513
         japantrend |  -.0018459   .0024769    -0.75   0.470    -.0072425    .0035508
   netherlandstrend |    .000226   .0003183     0.71   0.491    -.0004674    .0009195
       germanytrend |   .0001482   .0019461     0.08   0.941    -.0040919    .0043884
        russiatrend |  -.0013921   .0026118    -0.53   0.604    -.0070828    .0042987
         spaintrend |   .0011962   .0000906    13.21   0.000     .0009989    .0013936
        swedentrend |  -.0089841   .0042616    -2.11   0.057    -.0182692     .000301
           usatrend |   .0099164   .0108871     0.91   0.380    -.0138044    .0336373
            uktrend |   .0032485   .0020091     1.62   0.132     -.001129    .0076259
          ottotrend |  -.0129014   .0001728   -74.68   0.000    -.0132778    -.012525
              _cons |  -1.282939   2.715922    -0.47   0.645    -7.200426    4.634547
--------------------+----------------------------------------------------------------
            sigma_u |  12.167646
            sigma_e |  .28799108
                rho |  .99944011   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. xtreg universal RRkmip1 firstcruise_lib popul2 gdppcip2 literacy_qrt democracy austriahungarytrend chinatrend francetrend italytrend japantrend netherlandstrend germanytrend ru
> ssiatrend spaintrend swedentrend usatrend uktrend ottotrend if waryear==1, fe cluster(countryno);

Fixed-effects (within) regression               Number of obs      =      1046
Group variable: countryno                       Number of groups   =        13

R-sq:  within  = 0.7394                         Obs per group: min =         7
       between = 0.0852                                        avg =      80.5
       overall = 0.0637                                        max =       178

                                                F(6,12)            =         .
corr(u_i, Xb)  = -0.9998                        Prob > F           =         .

                                    (Std. Err. adjusted for 13 clusters in countryno)
-------------------------------------------------------------------------------------
                    |               Robust
          universal |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
            RRkmip1 |   10.85131   1.654265     6.56   0.000      7.24698    14.45565
    firstcruise_lib |  -.3486237   .4327724    -0.81   0.436    -1.291554    .5943063
             popul2 |  -3.905767   3.880082    -1.01   0.334    -12.35974    4.548206
           gdppcip2 |   .0388026    .032785     1.18   0.260    -.0326299    .1102351
       literacy_qrt |   .0789621   .0687728     1.15   0.273    -.0708809    .2288052
          democracy |   .2081503   .0770904     2.70   0.019     .0401848    .3761159
austriahungarytrend |   .0005319   .0003115     1.71   0.113    -.0001467    .0012105
         chinatrend |   .0853863   .0542592     1.57   0.142    -.0328343    .2036069
        francetrend |  -.0001364   .0005374    -0.25   0.804    -.0013072    .0010345
         italytrend |   .0046594   .0021881     2.13   0.055    -.0001081    .0094269
         japantrend |  -.0040664   .0026338    -1.54   0.149    -.0098049    .0016722
   netherlandstrend |  -.0003037   .0002666    -1.14   0.277    -.0008846    .0002772
       germanytrend |   .0025012   .0010384     2.41   0.033     .0002386    .0047637
        russiatrend |   .0031018   .0023177     1.34   0.206    -.0019481    .0081516
         spaintrend |   .0000392   .0000666     0.59   0.567    -.0001058    .0001842
        swedentrend |  -.0026957   .0023272    -1.16   0.269    -.0077663    .0023749
           usatrend |    .016785   .0062796     2.67   0.020      .003103     .030467
            uktrend |  -.0005891   .0004183    -1.41   0.184    -.0015005    .0003224
          ottotrend |  -.0001761   .0001599    -1.10   0.292    -.0005245    .0001723
              _cons |  -2.420554   1.264736    -1.91   0.080    -5.176177    .3350693
--------------------+----------------------------------------------------------------
            sigma_u |  45.908236
            sigma_e |  .13932253
                rho |  .99999079   (fraction of variance due to u_i)
-------------------------------------------------------------------------------------

. log close;
      name:  <unnamed>
       log:  C:\Users\scheve\Dropbox\war\WarMobilizationFinancingProject\RailroadPaper\Analysis\JEH_Replication_2\OSS_mobil_replication.log
  log type:  text
 closed on:  26 Nov 2013, 13:44:56
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